Direct manufacture of orthodontic appliance

Abstract

A method for additive manufacturing of an orthodontic appliance may include receiving a digital model of the appliance; processing the digital model of the appliance to modify the digital model based on the predicted deviation during manufacturing to generate a first updated digital model of the appliance; determining whether a predicted deviation of a physical appliance manufactured based on the first updated digital model of the appliance is acceptable; and outputting the first updated digital model of the appliance to manufacture the physical appliance through additive manufacturing of the physical appliance.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 269,832, filed on March 23, 2022, entitled “Direct Manufacturing of Orthodontic Appliances,” the entire contents of which are incorporated herein by reference. Background Art

[0002] Orthodontic and dental treatments using a series of patient-removable appliances (e.g., "appliances") are very useful for treating patients, particularly for treating malocclusion. Direct manufacturing of appliances, sometimes referred to as 3D printing, can reduce waste and increase production time compared to thermoforming appliances on directly manufactured molds. However, in at least some cases, direct manufacturing of appliances can have less than desirable results. Direct manufacturing can result in the manufacture of inaccurate appliances or appliances with defects that result in less than ideal orthodontic treatment.

[0003] Current appliances may also have less than ideal physical structures. For example, the bite ramps (biteramps) of the shell appliances and other appliance features have a consistent thickness, which may cause less than ideal movement forces or may wear prematurely due to the patient's chewing and biting forces acting on the features.

[0004] The methods and apparatus described herein may improve appliance manufacturing, including potentially improving the quality of appliances and the precision with which they are manufactured, which may result in increased predictability of the process and may result in reduced process time.

[0005] The methods and apparatus described herein may also improve appliance features and provide new ways of generating appliance shapes and features, which may result in increased patient comfort, increased patient compliance, increased appliance durability, increased predictability of treatment, and provide new ways of treating malocclusion. Summary of the invention

[0006] As will be described in greater detail below, the present disclosure describes various systems and methods for direct manufacturing of orthodontic appliances.

[0007] In addition, the systems and methods described herein can improve the functionality of a computing device by reducing the computing resources and overhead used to generate models of orthodontic appliances, and can improve the quality of manufactured appliances, thereby increasing the processing efficiency of the computing device and the resulting appliances relative to conventional methods. These systems and methods can also improve the field of orthodontic processing by improving the predictability of appliance manufacturing and processing. Incorporation by reference

[0008] All patents, applications, and publications mentioned and identified herein are incorporated by reference in their entirety and should be considered to be fully incorporated by reference even if mentioned elsewhere in this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] A better understanding of the features, advantages, and principles of the present disclosure will be obtained by referring to the following detailed description, which sets forth illustrative embodiments thereof and the accompanying drawings, and in which:

[0010] Figure 1 An exemplary tooth repositioning appliance or device is shown that may be worn by a patient to achieve incremental repositioning of individual teeth in a jaw, according to some embodiments.

[0011] Figure 2 A tooth repositioning system according to some embodiments is shown.

[0012] Figure 3 A method of orthodontic treatment using multiple appliances according to an embodiment is shown;

[0013] Figure 4 A method for digitally planning an orthodontic treatment according to an embodiment is shown;

[0014] Figure 5 shows a simplified block diagram of a data processing system according to an embodiment;

[0015] Figure 6 A method of generating instructions for manufacturing an appliance according to an embodiment is shown, compensating for deviations during manufacturing;

[0016] Figure 7 A method of generating instructions for manufacturing an appliance in real time according to an embodiment is shown, compensating for deviations during manufacturing;

[0017] Figure 8 Various aspects of a method for generating instructions for manufacturing an appliance in real time, compensating for deviations during manufacturing, according to an embodiment are shown;

[0018] Fig. 9 A method of generating instructions for manufacturing an appliance in real time according to an embodiment is shown, compensating for deviations during manufacturing;

[0019] Fig.10 A method of generating instructions for manufacturing an appliance according to an embodiment is shown, compensating for deviations during manufacturing;

[0020] Fig.11 A method of training a neural network for manufacturing an appliance according to an embodiment is shown, compensating for deviations during manufacturing;

[0021] Fig.12 A block diagram illustrating an example computing system capable of implementing one or more embodiments described and / or illustrated herein, according to an embodiment;

[0022] Fig.13 shows a block diagram of an example computing network capable of implementing one or more embodiments described and / or illustrated herein, according to an embodiment;

[0023] Fig.14A , 14B and 14C depicts an occlusal stability feature, such as an occlusal ramp, generated using a thickness map according to an embodiment;

[0024] Fig.15 depicts a thickness graph of an appliance according to an embodiment;

[0025] Fig.16 depicts a cross section of an occlusal portion of an appliance generated using a thickness map for intrusion or extrusion of teeth on respective teeth of a patient in accordance with an embodiment;

[0026] Fig.17A depicts cross-sections of occlusal and interproximal portions of an appliance generated using a thickness map in accordance with an embodiment;

[0027] Fig. 17B depicts a model of interproximal forces exerted on teeth by an appliance according to an embodiment;

[0028] Fig.18 Depicted are methods of generating and adjusting force distribution and generating thickness maps according to embodiments;

[0029] Fig.19A depicts the jaw of a patient being disoccluded according to an embodiment;

[0030] Fig.19B A method for generating a thickness map to deocclude a patient's jaw is depicted in accordance with an embodiment. DETAILED DESCRIPTION

[0031] The following detailed description provides a better understanding of the features and advantages of the invention described in this disclosure according to the embodiments disclosed herein. Although the detailed description includes many specific embodiments, these embodiments are provided by way of example only and should not be construed as limiting the scope of the invention disclosed herein.

[0032] Figure 1An exemplary tooth repositioning appliance 100 is shown, such as an appliance that can be worn by a patient to achieve incremental repositioning of a single tooth 102 in a jaw. The appliance can include a shell (e.g., a continuous polymer shell or a segmented shell) having a tooth-receiving cavity that receives the tooth and resiliently repositions the tooth. The appliance or (one or more) portions thereof can be indirectly manufactured using a physical model of the teeth. For example, an appliance (e.g., a polymer appliance) can be formed using a physical model of the teeth and a sheet of a suitable polymer material layer. The physical model of the teeth (e.g., a physical mold) can be formed by a variety of techniques, including 3D printing. The appliance can be formed by thermoforming the appliance on the physical model. In some embodiments, the physical appliance is directly manufactured from a digital model of the appliance, for example using additive manufacturing techniques. In some embodiments, the physical appliance can be created by various direct forming techniques, such as 3D printing. The appliance can fit on all teeth present in the upper or lower jaw, or on less than all teeth. The appliance can be specifically designed to accommodate the patient's teeth (e.g., the topology of the tooth-receiving cavity matches the topology of the patient's teeth), and can be manufactured based on a positive or negative model of the patient's teeth generated by an impression, scan, etc. Alternatively, the appliance can be a common appliance constructed to accommodate teeth, but it does not have to be shaped to match the topology of the patient's teeth. In some cases, only certain teeth accommodated by the appliance will be repositioned by the appliance, while other teeth can provide a base or anchoring area for holding the appliance in place when it applies force to one or more teeth that are the target of repositioning. In some cases, some or most, or even all of the teeth will be repositioned at a certain point during the treatment. The moved teeth can also be used as a base or anchor for holding the appliance when worn by the patient. In some embodiments, no wire or other device will be provided for holding the appliance in place on the teeth. However, in some cases, it may be desirable or necessary to provide a separate attachment or other anchoring element 104 on the tooth 102, wherein there is a corresponding socket or hole 106 in the appliance 100 so that the appliance can apply a selected force on the tooth. Many patents and patent applications assigned to Align Technology describe Examples of tooth-mounted attachments suitable for use with orthodontic appliances are described in patents and patent applications assigned to Align Technology, including, for example, U.S. Pat. Nos. 6,450,807 and 5,975,893, and on the company's website, which can be accessed on the World Wide Web (see, for example, URL "invisalign.com"). Examples of tooth-mounted attachments suitable for use with orthodontic appliances are also described in patents and patent applications assigned to Align Technology, including, for example, U.S. Pat. Nos. 6,309,215 and 6,830,450.

[0033] Figure 1A tooth repositioning system 101 is shown that includes multiple appliances 103A, 103B, 103C. Any appliance described herein may be designed and / or provided as part of a set of multiple appliances for use in a tooth repositioning system. Each appliance may be constructed so that a tooth receiving cavity has a geometry corresponding to an intermediate or final tooth arrangement intended for the appliance. By placing a series of incremental position adjustment appliances on the patient's teeth, the patient's teeth can be progressively repositioned from an initial tooth arrangement to a target tooth arrangement. For example, the tooth repositioning system 101 may include a first appliance 103A corresponding to an initial tooth arrangement, one or more intermediate appliances 103B corresponding to one or more intermediate arrangements, and a final appliance 103C corresponding to a target arrangement. The target tooth arrangement may be a planned final tooth arrangement selected for the patient's teeth at the end of all planned orthodontic treatments. Alternatively, the target arrangement can be one of a number of intermediate arrangements for the patient's teeth during the course of orthodontic treatment, which can include a variety of different treatment situations, including but not limited to situations where surgery is recommended, situations where interproximal reduction (IPR) is appropriate, situations where a progress check is scheduled, situations where anchor placement is optimal, situations where palate expansion is desired, situations involving restorative dentistry (e.g., inlays, onlays, crowns, bridges, implants, veneers, etc.), etc. As such, it should be understood that the target tooth arrangement can be any planned resulting arrangement of the patient's teeth after one or more incremental repositioning stages. Likewise, the initial tooth arrangement can be any initial arrangement of the patient's teeth after one or more incremental repositioning stages.

[0034] Optionally, in cases involving more complex motion or treatment planning, it may be beneficial to utilize auxiliary components (e.g., features, accessories, structures, devices, components, etc.) in conjunction with the orthodontic appliance. Examples of such accessories include, but are not limited to, elastics, wires, springs, rods, arch expanders, palatal expanders, bimaxillary blocks, bite blocks, bite ramps, mandibular advancement splints, bite plates, bridges, hooks, brackets, headgear tubes, springs, buffer tubes, palatal bars, frames, pin-tube devices, buccal shields, buccal arches, wire shields, lingual flanges and pads, lip pads or buffers, protrusions, divots, etc. In some embodiments, the appliances, systems, and methods described herein include improved orthodontic appliances having integrally formed features that are shaped to couple to, or replace, such auxiliary components.

[0035] Figure 3A method 300 of orthodontic treatment using multiple appliances according to many embodiments is shown. The method 300 can be practiced using any appliance or set of appliances described herein. In step 310, a first orthodontic appliance is applied to the patient's teeth so as to reposition the teeth from a first tooth arrangement to a second tooth arrangement. In step 320, a second orthodontic appliance is applied to the patient's teeth so as to reposition the teeth from the second tooth arrangement to a third tooth arrangement. As desired, the method 300 can be repeated using any suitable number of series of appliances and combinations thereof so as to incrementally reposition the patient's teeth from an initial arrangement to a target arrangement. The appliances can all be generated at the same stage or in groups or batches (e.g., at the beginning of a treatment stage), or one at a time, and the patient can wear each appliance until the pressure of each appliance on the teeth can no longer be felt, or until the maximum amount of tooth movement expressed for that given stage has been achieved. Multiple different (e.g., a set of) appliances can be designed and even manufactured before the patient wears any of the multiple appliances. After wearing the appliance for an appropriate period of time, the patient can replace the current appliance with the next appliance in the series until there are no more appliances remaining. Appliances are usually not fixed to the teeth, and patients can place and replace appliances at any time during the process (e.g., patient-removable appliances). The final appliance or several appliances in the series may have one or more geometries selected for overcorrecting the tooth arrangement. For example, one or more appliances may have a geometry that will (if fully realized) move a single tooth outside the tooth arrangement that has been selected as the "final". In order to compensate for potential recurrence after the repositioning method has been terminated, this overcorrection may be desirable (e.g., allowing a single tooth to move backward toward their pre-corrected position). Overcorrection can also be beneficial to speed up the correction rate (e.g., an appliance with a geometry positioned outside the desired intermediate or final position can cause a single tooth to shift toward the position at a greater rate). In such a case, the use of the appliance can be terminated before the tooth reaches the position defined by the appliance. In addition, overcorrection can be deliberately applied to compensate for any inaccuracies or limitations of the appliance.

[0036] Figure 4 A method 400 for digitally planning orthodontic treatment and / or design or manufacture of an appliance according to many embodiments is shown. The method 400 can be applied to any process described herein and can be performed by any suitable data processing system. Any embodiment of the appliance described herein can be designed or manufactured using the method 400.

[0037] In step 410, a digital representation of the patient's teeth is received. The digital representation may include surface topological data of the patient's oral cavity (including teeth, gingival tissue, etc.). The surface topological data may be generated by directly scanning the oral cavity, a physical model (positive or negative) of the oral cavity, or an impression of the oral cavity using a suitable scanning device (e.g., a handheld scanner, a desktop scanner, etc.).

[0038] In step 420, one or more treatment stages are generated based on the digital representation of the teeth. The treatment stages may be incremental repositioning stages of an orthodontic treatment program designed to move one or more of the patient's teeth from an initial tooth arrangement to a target arrangement. For example, the treatment stages may be generated by determining an initial tooth arrangement indicated by the digital representation, determining a target tooth arrangement, and determining a path of motion necessary for one or more teeth in the initial arrangement to achieve the target tooth arrangement. The path of motion may be optimized based on minimizing the total distance moved, preventing collisions between teeth, avoiding more difficult tooth movements, or any other suitable criteria.

[0039] In step 430, at least one orthodontic appliance is manufactured based on the generated processing stages. For example, a set of appliances can be manufactured to be worn sequentially by a patient to incrementally reposition the teeth from an initial arrangement to a target arrangement. Some appliances can be shaped to accommodate a tooth arrangement specified by one of the processing stages. Alternatively or in combination, some appliances can be shaped to accommodate a tooth arrangement that is different from the target arrangement for the corresponding processing stage. For example, as previously described herein, an appliance can have a geometry corresponding to an overcorrected tooth arrangement. Such an appliance can be used to ensure that an appropriate amount of force is applied to the teeth as the teeth approach or reach their desired target position for the processing stage. As another example, an appliance can be designed to apply a specific force system to the teeth, and the appliance may not have a geometry corresponding to any current or planned arrangement of the patient's teeth.

[0040] In some cases, the hierarchical arrangement of various arrangements or processing stages may not be necessary for the design and / or manufacture of the appliance. Figure 4 As shown by the dashed lines in , the design and / or manufacture of orthodontic appliances, and possibly specific orthodontic treatments, can include using a representation of a patient's teeth (e.g., receiving a digital representation of the patient's teeth 410), and then designing and / or manufacturing the orthodontic appliance based on the representation of the patient's teeth in an arrangement represented by the received representation.

[0041] Figure 55 is a simplified block diagram of a data processing system 1400 that can be used to perform the methods and processes described herein. The data processing system 500 typically includes at least one processor 502 that communicates with one or more peripheral devices via a bus subsystem 504. These peripheral devices typically include a storage subsystem 506 (a memory subsystem 508 and a file storage subsystem 514), a set of user interface input and output devices 518, and an interface 516 to an external network. This interface is schematically represented as a "network interface" block 516 and is coupled to corresponding interface devices in other data processing systems via a communication network interface 524. The data processing system 500 may include, for example, one or more computers, such as personal computers, workstations, mainframes, laptop computers, etc.

[0042] The user interface input device 518 is not limited to any particular device, and may generally include, for example, a keyboard, a pointing device, a mouse, a scanner, an interactive display, a touch pad, a joystick, etc. Similarly, a variety of user interface output devices may be used in the system of the present invention, and may include, for example, one or more of a printer, a display (e.g., visual, non-visual) system / subsystem, a controller, a projection device, an audio output, etc.

[0043] The storage subsystem 506 maintains the basic required programming, including computer readable media with instructions (e.g., operating instructions, etc.) and data structures. The program modules discussed herein are generally stored in the storage subsystem 506. The storage subsystem 506 generally includes a memory subsystem 508 and a file storage subsystem 514. The memory subsystem 508 generally includes a plurality of memories (e.g., RAM 510, ROM 512, etc.), which include computer readable memories for storing fixed instructions, instructions and data during program execution, basic input / output systems, etc. The file storage subsystem 514 provides persistent (non-volatile) storage for program and data files, and may include one or more removable or fixed drives or media, hard disks, floppy disks, CD-ROMs, DVDs, optical drives, etc. One or more storage systems, drives, etc. may be located at a remote location, such as via a server on a network or coupled via the Internet / World Wide Web. In this context, the term "bus subsystem" is generally used to include any mechanism for enabling the various components and subsystems to communicate with each other as intended, and may include various suitable components / systems that will be known or deemed suitable for use therein. It should be appreciated that the various components of the system may, but need not, be at the same physical location, but may be connected via various local or wide area network media, transmission systems, etc.

[0044] Scanner 520 includes any means for obtaining a digital representation (e.g., image, surface topology data, etc.) of a patient's teeth (e.g., by scanning a physical model of the teeth, such as a cast 521, by scanning an impression taken of the teeth, or by directly scanning the intraoral cavity), which may be obtained from the patient or from a treating professional, such as an orthodontist, and includes means for providing the digital representation to data processing system 500 for further processing. Scanner 520 may be located at a remote location relative to the other components of the system, and may communicate image data and / or information to data processing system 500, for example, via network interface 524. Manufacturing system 522 manufactures appliance 523 based on a treatment plan that includes data set information received from data processing system 500. Manufacturing machine 522 may, for example, be located at a remote location and receive data set information from data processing system 500 via network interface 524.

[0045] Figure 6 A method 600 of generating instructions for manufacturing an appliance is shown, compensating for deviations during manufacturing, according to embodiments discussed herein. The method 600 may begin at block 610. The method 600 may be performed prior to manufacturing of a physical appliance.

[0046] At block 620, component information is generated or received. The component information may be generated based on the treatment plan to move the patient's teeth from the first arrangement toward the second arrangement. The component information may include a three-dimensional model of the orthodontic appliance for use in the treatment planning phase. In some embodiments, the three-dimensional model may include slices of the three-dimensional model of the orthodontic appliance. These slices may be layers used to generate instructions to print, directly manufacture the orthodontic appliance.

[0047] At block 630, a deviation correction processor may modify the component information. The deviation correction processor may receive the component information generated or received at block 620. The component information may be considered a pre-processed model of an appliance or other orthodontic device that has not yet been processed to compensate for potential deviations from the model that may occur during manufacturing. The deviation correction processor may process the pre-processed model 640 in order to predict deviations of the manufactured appliance compared to the desired geometry of the digital three-dimensional model of the appliance.

[0048] The predictions can be based on analytical and / or numerical simulation techniques used to generate the prediction model. In some embodiments, the prediction model can be based on a model of partial differential equations that can be solved using various techniques, such as finite element or finite volume methods, for example, by simulating direct manufacture of the appliance, or from data generated by past simulations of appliance manufacture.

[0049] In some embodiments, the prediction model can be a machine learning model, such as a Bayesian model, a regression model, a decision tree algorithm, or a support vector machine or a neural network trained based on experimental data. The prediction model can be trained based on a comparison of the shape of a previously printed orthodontic appliance with the shape of a three-dimensional model of the orthodontic appliance. The printed orthodontic appliance can be digitally imaged in two or three dimensions, such as by CT scanning, x-ray radiography, etc. In some embodiments, the prediction model can use clustering techniques, pattern searching, or size reduction based on a comparison of previously designed and printed orthodontic appliances. Building a prediction model can include clustering of identified deviations, geometric patterns in appliances and their associated deviations, and size reduction to simplify analysis.

[0050] In some embodiments, clustering techniques can be used to cluster the types of deviations.Zero deviation regions of the appliance can be classified based on geometry or other factors.

[0051] When generating a prediction of the deviation of the manufactured appliance compared to the digital three-dimensional model of the appliance, the deviation correction processor and the prediction model may use one or more parameters 650, which may include variables. In some embodiments, the parameters may include the angle of the appliance. The angle may be the angle of the surface of the appliance relative to the build direction, such as the angle relative to the build platform on which the physical orthodontic appliance is built. In some embodiments, the angle may be the angle of the surface of the appliance relative to the plane or axis of the appliance, such as the occlusal plane of the appliance. In some embodiments, the parameters may include the thickness of the appliance. The thickness of the appliance may be measured perpendicular to the outer surface of the appliance, parallel to the build surface, perpendicular to the build surface, or relative to a portion of the appliance itself. In some embodiments, the thickness may be the thickness of the appliance from the surface of the appliance that faces outward from the tooth receiving cavity or is not part of the tooth receiving cavity to the surface of the tooth receiving cavity, such as the inner surface that defines the inner shape of the tooth receiving cavity.

[0052] In some embodiments, the parameters may include a cross-sectional aspect ratio of the appliance in a plane. In some embodiments, the plane may be a plane parallel to the build surface on which the appliance is printed or used for direct manufacturing, or a plane perpendicular to the build direction, sometimes represented as the Z direction in direct manufacturing. The cross-sectional aspect ratio may be determined based on the ratio of the longest overall length dimension of the appliance in the plane to the longest length dimension perpendicular to the longest overall length dimension. In some embodiments, the cross-sectional aspect ratio may be a feature of the appliance rather than a feature of the entire plane of the appliance. In direct manufacturing, a physical object may be constructed layer by layer, sometimes referred to as slices, each slice being generated based on a cross section of a three-dimensional model and having a certain thickness. The plane used to determine the cross-sectional aspect ratio or other features in the plane may be such a slice.

[0053] In some embodiments, the parameters may include the position of the appliance in the dental arch. For example, in some embodiments, the position may be labeled as posterior, anterior, buccal, and / or lingual. In some embodiments, the position may be based on a tooth-by-tooth basis, such as by identifying a particular tooth receiving cavity position as the upper left central incisor or the lower left central incisor. In some embodiments, the position may also include buccal or lingual or occlusal surfaces and / or gum lines.

[0054] In some embodiments, the parameters may include the material used to make the physical implement, the age of the material, the moisture content of the material, the color of the material, the viscosity of the material, and other material properties.

[0055] In some embodiments, the parameters may include a manufacturing method for manufacturing the physical appliance. In some embodiments, the parameters may include manufacturing settings for the manufacturing process. The manufacturing settings may include an expected ambient temperature, an expected material temperature, an expected ambient and / or manufacturing chamber humidity, an expected exposure time, an expected exposure wavelength, an expected exposure intensity, an expected nozzle temperature, an expected material flow rate, an expected extrusion pressure, and other expected settings for the printing process.

[0056] In some embodiments, the parameters may include cleaning settings. In some direct manufacturing processes such as SLA, after the initial fabrication of the tool, a fluid bath of other devices is used to remove excess resin or other material from the printed part. The cleaning settings may include bath temperature, fluid type, fluid flow rate, fluid pressure, bath lighting type, cleaning force, and other cleaning parameters.

[0057] In some embodiments, the parameters may include post-curing settings or post-processing settings. In direct manufacturing processes such as SLA, components such as orthodontic appliances may undergo additional curing, storage, or other processing after initial manufacturing and cleaning. In some embodiments, post-curing settings or post-processing settings may include ambient temperature, material temperature, exposure time, exposure wavelength, exposure intensity, nozzle temperature, material flow rate, extrusion pressure, and other settings.

[0058] In some embodiments, parameters may also include aspects of supports that may be generated during the manufacturing process to support the appliance. Supports may be manufactured during the manufacturing process and subsequently removed from the manufactured appliance. Supports may be generated to extend from a base or plate of a manufacturing machine, a first layer of a print, or from one portion of the appliance to another portion of the appliance that may not otherwise be supported. Support parameters may include support designs, such as support types, including grid supports that may be vertical walls or columns, and tree supports that include a trunk extending from a base and branches extending from the trunk to the appliance. Support parameters may also include support density, such as the number of supports per unit area, the shape of the supports, and the position of the supports.

[0059] In some embodiments, for each case run through the deviation correction preprocessor, where each case can be an appliance for an orthodontic treatment phase, the deviation correction processor can warn for or otherwise identify and quantify predictable deviations. In addition, the deviation correction preprocessor can match clustered deviation types with the closest class having zero deviation geometry or near zero deviation geometry, such as within acceptable deviations. By using the closest class with zero deviation geometry for the identified clustered deviation types, the preprocessor can modify the geometry of the appliance to reduce or eliminate expected deviations within the physics.

[0060] At block 640, the deviation correction preprocessor may generate a post-processing model based on the pre-processing model and the parameters. In some embodiments, the post-processing model may include information related to expected deviations of the physical model directly after fabrication.

[0061] At block 660, the deviation correction preprocessor determines whether the expected deviation is acceptable. The deviation correction preprocessor may review various aspects of the post-processed model to determine whether the deviation is acceptable. In some embodiments, the deviation correction preprocessor may review the appliance thickness, the deviation of the expected physical appliance surface position compared to the corresponding position, and the three-dimensional model. In some embodiments, the deviation correction preprocessor determines the deviation based on the expected physical component geometry compared to the expected physical component geometry (such as defined by the geometry of the three-dimensional digital model of the appliance).

[0062] If the deviation is acceptable, such as within a threshold of acceptable deviation, the post-processing model or instructions for making the post-processing model can be sent to the manufacturing machine for manufacturing. In some embodiments, the pre-processing model can have an acceptable expected deviation. In such embodiments, the pre-processing model or instructions for making the pre-processing model can be sent to the manufacturing machine for manufacturing. In some embodiments, if the deviation is unacceptable, the part can be sent back for additional correction.

[0063] At block 670 , the manufacturing machine manufactures the orthodontic appliance using one or more processes disclosed herein.

[0064] Figure 7 A method 700 for generating instructions in real time for manufacturing an appliance, compensating for deviations during manufacturing, according to embodiments discussed herein is shown. The method 700 may begin at block 710. Some or all of the method 700 may be performed before or during manufacturing of an orthodontic appliance.

[0065] At block 720, component information is generated or received. The component information may be generated based on the treatment plan to move the patient's teeth from the first arrangement toward the second arrangement. The component information may include a three-dimensional model of the orthodontic appliance for the stage of the treatment plan. In some embodiments, the three-dimensional model may include slices of the three-dimensional model of the orthodontic appliance. The slices may be layers for generating instructions to print, directly manufacture the orthodontic appliance.

[0066] At block 730, the real-time deviation correction processor system may modify the component information. One difference between the real-time correction processor system described above and the deviation processor system 630 is that the real-time deviation correction processor system may use data received during manufacture of the appliance (such as during manufacture of past slices of the appliance) to predict and correct for deviations in to-be-printed slices of future or currently manufactured appliances.

[0067] The real-time deviation correction processor can receive the component information generated or received at box 620. The component information can be considered a pre-processed model of the appliance or other orthodontic device that has not yet been processed to compensate for potential deviations from the model that may occur during manufacturing, or can be a post-processed model, such as the post-processed model output at box 670 of method 600. In some embodiments, the real-time deviation correction processor system can receive a slice of the digital model of the appliance. The real-time deviation correction processor can process the received model using real-time manufacturing information acquired during the manufacturing process. In some embodiments, the real-time manufacturing information can be used in method 700 within seconds or minutes after it is acquired. In some embodiments, such as during SLA manufacturing or other directional manufacturing processes (direction fabrication process), data acquired for a slice of the model being manufactured can be used by the real-time deviation correction processor system to correct the next slice to be manufactured.

[0068] The predictions can be based on analytical and / or numerical simulation techniques used to generate the prediction model. In some embodiments, the prediction model can be based on a model of partial differential equations that can be solved using various techniques, such as finite element or finite volume methods, for example, by simulating direct manufacture of the appliance, or from data generated by past simulations of appliance manufacture.

[0069] In some embodiments, the prediction model can be a machine learning model, such as a Bayesian model, a regression model, a decision tree algorithm, or a support vector machine or a neural network trained based on experimental data. The prediction model can be trained based on a comparison of the shape of a previously printed orthodontic appliance or a slice thereof with the shape of a three-dimensional model of the orthodontic appliance. The printed orthodontic appliance can be digitally imaged in two or three dimensions, such as by CT scanning, X-ray radiography, etc. In some embodiments, the prediction model can use clustering techniques, pattern searching, or size reduction based on a comparison of a previously designed and printed orthodontic appliance or a slice thereof.

[0070] Building a predictive model can include identifying clusters of deviations, geometric patterns in the appliance and their associated deviations, and reductions in size to simplify analysis. In some embodiments, clustering techniques can be used to cluster types of deviations, and zero deviation areas of the appliance can be classified based on geometry or other factors.

[0071] When generating a prediction of the deviation of the manufactured appliance compared to the digital three-dimensional model of the appliance, the deviation correction processor and its prediction model may use one or more parameters, which may include variables. In some embodiments, the parameter may include the angle of the appliance. The angle may be the angle of the surface of the appliance relative to the build direction, such as the angle relative to the build platform on which the physical orthodontic appliance is built. In some embodiments, the angle may be the angle of the surface of the appliance relative to the plane or axis of the appliance, such as the occlusal plane of the appliance. In some embodiments, the parameter may include the thickness of the appliance. The thickness of the appliance may be measured perpendicular to the outer surface of the appliance, parallel to the build surface, perpendicular to the build surface, or relative to a portion of the appliance itself. In some embodiments, the thickness may be the thickness of the appliance from the surface of the appliance that faces outward from the tooth receiving cavity or is not part of the tooth receiving cavity to the surface of the tooth receiving cavity, such as the internal surface that defines the internal shape of the tooth receiving cavity.

[0072] In some embodiments, the parameters may include a cross-sectional aspect ratio of the appliance in a plane. In some embodiments, the plane may be a plane parallel to the build surface on which the appliance is printed or used for direct manufacturing, or a plane perpendicular to the build direction, sometimes represented as the Z direction in direct manufacturing. The cross-sectional aspect ratio may be determined based on the ratio of the longest overall length dimension of the appliance in the plane to the longest length dimension perpendicular to the longest overall length dimension. In some embodiments, the cross-sectional aspect ratio may be a feature of the appliance rather than a feature of the entire plane of the appliance. In direct manufacturing, a physical object may be constructed layer by layer, sometimes referred to as slices, each slice being generated based on a cross section of a three-dimensional model and having a certain thickness. The plane used to determine the cross-sectional aspect ratio or other features in the plane may be such a slice.

[0073] In some embodiments, the parameters may include the location of the appliance in the dental arch. For example, in some embodiments, the location may be labeled as posterior, anterior, buccal, and / or lingual. In some embodiments, the location may be based on a tooth-by-tooth basis, such as by identifying a particular tooth receiving cavity location as the upper left central incisor or the lower left central incisor. In some embodiments, the location may also include buccal or lingual or occlusal surfaces and / or gum lines.

[0074] In some embodiments, the parameters may include the material used to make the physical implement, the age of the material, the moisture content of the material, the color of the material, the viscosity of the material, and other material properties.

[0075] In some embodiments, the parameters may include a manufacturing method for manufacturing the physical appliance. In some embodiments, the parameters may include real-time manufacturing information from the manufacturing process, such as information collected by embedded sensors 780. The real-time manufacturing information may include real-time ambient temperature, real-time material temperature, real-time ambient and / or manufacturing chamber humidity, real-time exposure time, real-time exposure wavelength, real-time exposure intensity, real-time nozzle temperature, real-time material flow rate, real-time extrusion pressure, and other real-time information.

[0076] The sensor 780 may include a temperature sensor, a humidity sensor, a viscosity sensor, a moisture sensor, a pressure sensor, a light sensor, and other sensors.

[0077] In some embodiments, real-time manufacturing information may include images or scans of printed parts as they are manufactured. Images and scans may include 2D images of recently printed slices or 3D scan data of parts with a focal plane parallel to the build platform on which the part is manufactured.

[0078] In some embodiments, the parameters may include cleaning settings. In some direct manufacturing processes such as SLA, after the initial fabrication of the tool, a fluid bath of other devices is used to remove excess resin or other material from the printed part. The cleaning settings may include bath temperature, fluid type, fluid flow rate, fluid pressure, bath lighting type, cleaning force, and other cleaning parameters.

[0079] In some embodiments, the parameters may include post-curing settings or post-processing settings. In some direct manufacturing processes such as SLA, components such as orthodontic appliances may undergo additional curing, storage, or other processing after initial manufacturing and cleaning. In some embodiments, the post-curing settings or post-processing settings may include ambient temperature, material temperature, exposure time, exposure wavelength, exposure intensity, nozzle temperature, material flow rate, extrusion pressure, and other settings.

[0080] In some embodiments, for each case run through the deviation correction preprocessor, where each case can be an appliance for an orthodontic treatment phase, the deviation correction processor can warn for a predictable deviation or otherwise identify a predictable deviation and quantify the deviation. In addition, the deviation correction preprocessor can match the clustered deviation types with the closest category having a zero deviation geometry or a near zero deviation geometry, such as within an acceptable deviation. By using the closest category with a zero deviation geometry for the identified clustered deviation types, the preprocessor can modify the geometry of the appliance to reduce or eliminate the expected deviation within the physics.

[0081] At block 740, the real-time deviation correction preprocessor can generate a post-processing model based on the received model and parameters. In some embodiments, the post-processing model can include information related to expected deviations from the physical model directly after manufacturing. In some embodiments, the post-processing model can be a model of the entire appliance, while in some embodiments, the post-processing model can be a model of a slice of the appliance.

[0082] At block 750, the deviation correction preprocessor determines whether the expected deviation is acceptable. The deviation correction preprocessor may review various aspects of the post-processed model to determine whether the deviation is acceptable. In some embodiments, the deviation correction preprocessor may review the appliance thickness, the deviation of the expected physical appliance surface position compared to the corresponding position, and the three-dimensional model. In some embodiments, the deviation correction preprocessor determines the deviation based on the expected physical component geometry compared to the expected physical component geometry (such as defined by the geometry of the three-dimensional digital model of the appliance).

[0083] If the deviation is acceptable, such as within a threshold of acceptable deviation, then at block 770, the post-processing model or instructions for making the post-processing model may be sent to a manufacturing machine for manufacturing. In some embodiments, the pre-processing model may have an acceptable expected deviation. In such embodiments, the pre-processing model or instructions for making the pre-processing model may be sent to a manufacturing machine for manufacturing. In some embodiments, if the deviation is unacceptable, then at block 760, the part or slices thereof may be corrected or sent to reduce the predicted deviation.

[0084] Figure 8 Various aspects of a method 785 for generating instructions for manufacturing an appliance in real time, compensating for deviations during manufacturing, according to embodiments discussed herein are shown. The method 785 may be Figure 7 Real-time prediction model 740.

[0085] At block 786 , a slice N of a tool being manufactured or to be manufactured is loaded or otherwise received.

[0086] At block 787 , a slice N of the device is manufactured using one or more of the methods discussed herein.

[0087] At box 788, sensor data is collected during the manufacture of slice N, and in some embodiments, sensor data is collected during the manufacture of slice N-1. The sensor data may include an image of the printed slice taken with a focal plane parallel to the plane of the slice, such as parallel to the build platform or build plane, sometimes referred to as the XY plane in direct manufacturing. For example, for DLP-based or laser-based SLA-based aligner manufacturing, ambient and local temperature sensors and IR surface temperature sensors can be used to provide multi-dimensional data to the predictive model. In addition, a relative viscosity sensor can continuously monitor the viscosity of the resin during layer-by-layer manufacturing and provide the data as input to the predictive model.

[0088] At block 789, the printed slice is compared to the digital model of the slice loaded at block 786. If the printed slice deviates from the geometry of the digital model of the slice by less than a predetermined amount, the process proceeds to block 792, where slice N+1 is loaded. If the printed slice deviates from the geometry of the digital model of the slice by more than a predetermined amount, the process proceeds to block 790.

[0089] As another example of manufacturing an appliance with a peel-based mechanism, the peel force of the component at each layer of the process can be determined based on FEA or analytical modeling of the system and sensors, such as optical diffraction based sensors or contact based sensors. The peel force of each layer can be determined during the printing process, and if the adhesion exceeds the design limit for that stage of manufacturing, the machine parameters affecting the adhesion can be modified in real time to ensure that no deflection is observed. In some embodiments, the adhesion can vary based on layer height or number of layers. The manufacturing speed and exposure time of each layer can also be dynamically varied based on manufacturing parameters and expected peel strength to minimize or reduce manufacturing time.

[0090] At block 790 , the predictive model may be updated to correct for actual deviations discovered during manufacturing.

[0091] At box 791, the updated prediction model can be run on slice n+1 before loading it into box 786.

[0092] In some embodiments, the slices may be reprocessed and the reprocessed slices may be reprinted at blocks 790 and 791. For example, deviations in printed slice N may be corrected or repaired by reprinting the same slice N layers to increase support, thicken certain areas of the part to mitigate deformation, or correct other defects or deviations.

[0093] Fig. 9A method 900 is shown for generating instructions for manufacturing an appliance in real time, compensating for deviations during manufacturing, according to embodiments discussed herein. The method 900 may include some or all of the methods 600, 700, and 785. The method 900 may begin at block 910.

[0094] At block 920, component information is generated or received. The component information may be generated based on the treatment plan to move the patient's teeth from a first arrangement toward a second arrangement. The component information may include a three-dimensional model of the orthodontic appliance for the stage of the treatment plan. In some embodiments, the three-dimensional model may include slices of the three-dimensional model of the orthodontic appliance. These slices may be layers for generating instructions to print, directly manufacture the orthodontic appliance. Block 920 may also perform various aspects of blocks 620 and 720 discussed herein.

[0095] At box 930, the deviation correction processor can modify the component information. Box 930 can perform various aspects of box 930. The deviation correction processor can receive the component information generated or received at box 720. The component information can be considered as a pre-processed model of the appliance or other orthodontic device that has not yet been processed to compensate for potential deviations from the model that may occur during manufacturing. The deviation correction processor can process the pre-processed model 940 to predict the deviation of the manufactured appliance compared to the desired geometry of the digital three-dimensional model of the appliance. The pre-processed model 940 can be the same as the pre-processed model 640.

[0096] The predictions can be based on analytical and / or numerical simulation techniques used to generate the prediction model. In some embodiments, the prediction model can be based on a model of partial differential equations that can be solved using various techniques, such as finite element or finite volume methods, for example, by simulating direct manufacture of the appliance, or from data generated by past simulations of appliance manufacture.

[0097] In some embodiments, the prediction model can be a machine learning model, such as a Bayesian model, a regression model, a decision tree algorithm, or a support vector machine or neural network trained based on experimental data. The prediction model can be trained based on a comparison of the shape of a previously printed orthodontic appliance with the shape of a three-dimensional model of the orthodontic appliance. The printed orthodontic appliance can be digitally imaged in two or three dimensions, such as by CT scanning, x-ray radiography, etc. In some embodiments, the prediction model can use clustering techniques, pattern searching, or size reduction based on a comparison of previously designed and printed orthodontic appliances. Building a prediction model can include clustering of identified deviations, geometric patterns in appliances and their associated deviations, and size reduction to simplify analysis.

[0098] In some embodiments, clustering techniques can be used to cluster the types of deviations.Zero deviation regions of the appliance can be classified based on geometry or other factors.

[0099] When generating a prediction of the deviation of the manufactured appliance compared to the digital three-dimensional model of the appliance, the deviation correction processor and the prediction model can use one or more parameters 960, which can include variables. Parameters 960 can be the same as parameters 650. In some embodiments, the parameters can include the angle of the appliance. The angle can be the angle of the surface of the appliance relative to the build direction, such as the angle relative to the build platform on which the physical orthodontic appliance will be built. In some embodiments, the angle can be the angle of the surface of the appliance relative to the plane or axis of the appliance, such as the occlusal plane of the appliance. In some embodiments, the parameters can include the thickness of the appliance. The thickness of the appliance can be measured perpendicular to the outer surface of the appliance, parallel to the build surface, perpendicular to the build surface, or relative to a portion of the appliance itself. In some embodiments, the thickness can be the thickness of the appliance from the surface of the appliance that faces outward from the tooth receiving cavity or is not part of the tooth receiving cavity to the surface of the tooth receiving cavity, the surface of the tooth receiving cavity such as the internal surface that defines the internal shape of the tooth receiving cavity.

[0100] In some embodiments, the parameters may include a cross-sectional aspect ratio of the appliance in a plane. In some embodiments, the plane may be a plane parallel to the build surface on which the appliance is printed or used for direct manufacturing, or a plane perpendicular to the build direction, sometimes represented as the Z direction in direct manufacturing. The cross-sectional aspect ratio may be determined based on the ratio of the longest overall length dimension of the appliance in the plane to the longest length dimension perpendicular to the longest overall length dimension. In some embodiments, the cross-sectional aspect ratio may be a feature of the appliance rather than a feature of the entire plane of the appliance. In direct manufacturing, a physical object may be constructed layer by layer, sometimes referred to as slices, each slice being generated based on a cross section of a three-dimensional model and having a certain thickness. The plane used to determine the cross-sectional aspect ratio or other features in the plane may be such a slice.

[0101] In some embodiments, the parameters may include the location of the appliance in the dental arch. For example, in some embodiments, the location may be labeled as posterior, anterior, buccal, and / or lingual. In some embodiments, the location may be based on a tooth-by-tooth basis, such as by identifying a particular tooth receiving cavity location as the upper left central incisor or the lower left central incisor. In some embodiments, the location may also include buccal or lingual or occlusal surfaces and / or gum lines.

[0102] In some embodiments, the parameters may include the material used to make the physical implement, the age of the material, the moisture content of the material, the color of the material, the viscosity of the material, and other material properties.

[0103] In some embodiments, the parameters may include a manufacturing method for manufacturing the physical appliance. In some embodiments, the parameters may include manufacturing settings for the manufacturing process. The manufacturing settings may include an expected ambient temperature, an expected material temperature, an expected ambient and / or manufacturing chamber humidity, an expected exposure time, an expected exposure wavelength, an expected exposure intensity, an expected nozzle temperature, an expected material flow rate, an expected extrusion pressure, and other expected settings for the printing process.

[0104] In some embodiments, the parameters may include cleaning settings. In some direct manufacturing processes such as SLA, after the initial fabrication of the tool, a fluid bath of other devices is used to remove excess resin or other material from the printed part. The cleaning settings may include bath temperature, fluid type, fluid flow rate, fluid pressure, bath lighting type, cleaning force, and other cleaning parameters.

[0105] In some embodiments, the parameters may include post-curing settings or post-processing settings. In direct manufacturing processes such as SLA, components such as orthodontic appliances may undergo additional curing, storage, or other processing after initial manufacturing and cleaning. In some embodiments, post-curing settings or post-processing settings may include ambient temperature, material temperature, exposure time, exposure wavelength, exposure intensity, nozzle temperature, material flow rate, extrusion pressure, and other settings.

[0106] In some embodiments, for each case run through the deviation correction preprocessor, where each case can be an appliance for an orthodontic treatment phase, the deviation correction processor can warn for a predictable deviation or otherwise identify a predictable deviation and quantify the deviation. In addition, the deviation correction preprocessor can match the clustered deviation types with the closest category having a zero deviation geometry or a near zero deviation geometry, such as within an acceptable deviation. By using the closest category with a zero deviation geometry for the identified clustered deviation types, the preprocessor can modify the geometry of the appliance to reduce or eliminate the expected deviation within the physics.

[0107] At block 940 , the deviation correction preprocessor can generate a post-processing model based on the pre-processing model and the parameters. In some embodiments, the post-processing model can include information related to expected deviations of the physical model directly after manufacturing. Block 940 can perform various aspects of block 640 .

[0108] At block 950, the deviation correction preprocessor determines whether the expected deviation is acceptable. Block 950 may perform various aspects of block 660. The deviation correction preprocessor may review various aspects of the post-processed model to determine whether the deviation is acceptable. In some embodiments, the deviation correction preprocessor may review the appliance thickness, the deviation of the expected physical appliance surface position compared to the corresponding position, and the three-dimensional model. In some embodiments, the deviation correction preprocessor determines the deviation based on the expected physical component geometry compared to the expected physical component geometry (such as defined by the geometry of the three-dimensional digital model of the appliance).

[0109] If the deviation is acceptable, such as within a threshold of acceptable deviation, the post-processing model or instructions for making the post-processing model can be sent to a manufacturing machine for manufacturing, and / or to a real-time deformation correction system 970. In some embodiments, the pre-processing model can have an acceptable expected deviation. In such an embodiment, the pre-processing model or instructions for making the pre-processing model can be sent to a manufacturing machine for manufacturing. In some embodiments, if the deviation is unacceptable, the part can be sent back for additional correction.

[0111] At block 970, the real-time deviation correction processor system may modify the component information. One difference between the real-time correction processor system described above and the deviation processor system 930 is that the real-time deviation correction processor system may use data received during the manufacture of the appliance (such as during the manufacture of past slices of the appliance) to predict and correct deviations for future or currently manufactured slices to be printed. Some of all aspects of method 785 may be performed by a real-time deformation correction system.

[0112] The real-time deviation correction processor can receive the component information generated or output at box 930. The component information can be considered a pre-processed model of the appliance or other orthodontic device that has not yet been processed to compensate for potential deviations from the model that may occur during manufacturing, or can be a post-processed model, such as the post-processed model output at box 940. In some embodiments, the real-time deviation correction processor system can receive a slice of the digital model of the appliance. The real-time deviation correction processor can process the received model using real-time manufacturing information acquired during the manufacturing process. In some embodiments, the real-time manufacturing information can be used in method 900 within seconds or minutes of its acquisition. In some embodiments, such as during SLA manufacturing or other directional manufacturing processes, data acquired for a slice of the model being manufactured can be used by the real-time deviation correction processor system to correct the next slice to be manufactured.

[0113] The predictions can be based on analytical and / or numerical simulation techniques used to generate the prediction model. In some embodiments, the prediction model can be based on a model of partial differential equations that can be solved using various techniques, such as finite element or finite volume methods, for example, by simulating direct manufacture of the appliance, or from data generated by past simulations of appliance manufacture.

[0114] In some embodiments, the prediction model can be a machine learning model, such as a Bayesian model, a regression model, a decision tree algorithm, or a support vector machine or neural network trained based on experimental data. The prediction model can be trained based on a comparison of the shape of a previously printed orthodontic appliance or a slice thereof with the shape of a three-dimensional model of the orthodontic appliance. The printed orthodontic appliance can be digitally imaged in two or three dimensions, such as by CT scanning, X-ray radiography, etc. In some embodiments, the prediction model can use clustering techniques, pattern searching, or size reduction based on a comparison of a previously designed and printed orthodontic appliance or a slice thereof.

[0115] Building a predictive model can include identifying clusters of deviations, geometric patterns in the appliance and their associated deviations, and reductions in size to simplify analysis. In some embodiments, clustering techniques can be used to cluster types of deviations, and zero deviation areas of the appliance can be classified based on geometry or other factors.

[0116] When generating a prediction of the deviation of the manufactured appliance compared to the digital three-dimensional model of the appliance, the deviation correction processor and its prediction model may use one or more parameters, which may include variables. In some embodiments, the parameter may include the angle of the appliance. The angle may be the angle of the surface of the appliance relative to the build direction, such as the angle relative to the build platform on which the physical orthodontic appliance is built. In some embodiments, the angle may be the angle of the surface of the appliance relative to the plane or axis of the appliance, such as the occlusal plane of the appliance. In some embodiments, the parameter may include the thickness of the appliance. The thickness of the appliance may be measured perpendicular to the outer surface of the appliance, parallel to the build surface, perpendicular to the build surface, or relative to a portion of the appliance itself. In some embodiments, the thickness may be the thickness of the appliance from the surface of the appliance that faces outward from the tooth receiving cavity or is not part of the tooth receiving cavity to the surface of the tooth receiving cavity, such as the internal surface that defines the internal shape of the tooth receiving cavity.

[0117] In some embodiments, the parameters may include a cross-sectional aspect ratio of the appliance in a plane. In some embodiments, the plane may be a plane parallel to the build surface on which the appliance is printed or used for direct manufacturing, or a plane perpendicular to the build direction, sometimes represented as the Z direction in direct manufacturing. The cross-sectional aspect ratio may be determined based on the ratio of the longest overall length dimension of the appliance in the plane to the longest length dimension perpendicular to the longest overall length dimension. In some embodiments, the cross-sectional aspect ratio may be a feature of the appliance rather than a feature of the entire plane of the appliance. In direct manufacturing, a physical object may be constructed layer by layer, sometimes referred to as slices, each slice being generated based on a cross section of a three-dimensional model and having a certain thickness. The plane used to determine the cross-sectional aspect ratio or other features in the plane may be such a slice.

[0118] In some embodiments, the parameters may include the location of the appliance in the dental arch. For example, in some embodiments, the location may be labeled as posterior, anterior, buccal, and / or lingual. In some embodiments, the location may be based on a tooth-by-tooth basis, such as by identifying a particular tooth receiving cavity location as the upper left central incisor or the lower left central incisor. In some embodiments, the location may also include buccal or lingual or occlusal surfaces and / or gum lines.

[0119] In some embodiments, the parameters may include the material used to make the physical implement, the age of the material, the moisture content of the material, the color of the material, the viscosity of the material, and other material properties.

[0120] In some embodiments, the parameters may include a manufacturing method for manufacturing the physical appliance. In some embodiments, the parameters may include real-time manufacturing information from the manufacturing process, such as information collected by embedded sensors 988. The real-time manufacturing information may include real-time ambient temperature, real-time material temperature, real-time ambient and / or manufacturing chamber humidity, real-time exposure time, real-time exposure wavelength, real-time exposure intensity, real-time nozzle temperature, real-time material flow rate, real-time extrusion pressure, and other real-time information.

[0121] Sensors 988 may include temperature sensors, humidity sensors, viscosity sensors, moisture sensors, pressure sensors, light sensors, and other sensors.

[0122] In some embodiments, real-time manufacturing information may include images or scans of printed parts as they are manufactured. Images and scans may include 2D images of recently printed slices with a focal plane parallel to the build platform on which the part is manufactured, or 3D scan data of the part.

[0123] In some embodiments, the parameters may include cleaning settings. In some direct manufacturing processes such as SLA, after the initial fabrication of the tool, a fluid bath for other devices is used to remove excess resin or other material from the printed part. The cleaning settings may include bath temperature, fluid type, fluid flow rate, fluid pressure, bath lighting type, cleaning force, and other cleaning parameters.

[0124] In some embodiments, the parameters may include post-curing settings or post-processing settings. In direct manufacturing processes such as SLA, components such as orthodontic appliances may undergo additional curing, storage, or other processing after initial manufacturing and cleaning. In some embodiments, post-curing settings or post-processing settings may include ambient temperature, material temperature, exposure time, exposure wavelength, exposure intensity, nozzle temperature, material flow rate, extrusion pressure, and other settings.

[0125] In some embodiments, for each case run through the deviation correction preprocessor, where each case can be an appliance for an orthodontic treatment phase, the deviation correction processor can warn for a predictable deviation or otherwise identify a predictable deviation and quantify the deviation. In addition, the deviation correction preprocessor can match the clustered deviation types with the closest category having a zero deviation geometry or a near zero deviation geometry, such as within an acceptable deviation. By using the closest category with a zero deviation geometry for the identified clustered deviation types, the preprocessor can modify the geometry of the appliance to reduce or eliminate the expected deviation within the physics.

[0126] At block 980, the real-time deviation correction preprocessor can generate a post-processing model based on the received model and parameters. In some embodiments, the post-processing model can include information related to expected deviations from the physical model directly after manufacturing. In some embodiments, the post-processing model can be a model of the entire appliance, while in some embodiments, the post-processing model can be a model of a slice of the appliance.

[0127] At block 982, the deviation correction preprocessor determines whether the expected deviation is acceptable. The deviation correction preprocessor may review various aspects of the post-processed model to determine whether the deviation is acceptable. In some embodiments, the deviation correction preprocessor may review the appliance thickness, the deviation of the expected physical appliance surface position compared to the corresponding position, and the three-dimensional model. In some embodiments, the deviation correction preprocessor determines the deviation based on the expected physical component geometry compared to the expected physical component geometry (such as defined by the geometry of the three-dimensional digital model of the appliance).

[0128] If the deviation is acceptable, such as within a threshold of acceptable deviation, the post-processing model or instructions for making the post-processing model can be sent to a manufacturing machine for manufacturing at box 986. In some embodiments, the pre-processing model can have an acceptable expected deviation. In such embodiments, the pre-processing model or instructions for making the pre-processing model can be sent to a manufacturing machine for manufacturing. In some embodiments, if the deviation is unacceptable, the part or its slice can be corrected or sent to reduce the predicted deviation at box 984.

[0129] Fig.10 A method 1000 of generating instructions for manufacturing an appliance is shown, compensating for deviations during manufacturing, according to embodiments discussed herein.

[0130] At block 1040, a prediction model is used to predict the deviation of the manufactured appliance or appliance slice from the desired appliance shape or the 3D digital model of the appliance shape. The prediction model can be developed based on past experience. For example, the model can be constructed using the digital model of the appliance 1010, the manufacturing settings used to manufacture the digital model 1020, and the image or three-dimensional model of the manufactured appliance 1030.

[0131] The digital model 1010 is generated based on a treatment plan to move the patient's teeth from a first arrangement toward a second arrangement. The model 1010 may include a three-dimensional model of an orthodontic appliance for use in the treatment planning phase. In some embodiments, the three-dimensional model may include slices of the three-dimensional model of the orthodontic appliance. These slices may be layers for generating instructions to print, directly manufacture the orthodontic appliance.

[0132] Manufacturing settings 1020 may include settings used to manufacture the appliance and / or data collected during the manufacture of the appliance, such as described above with respect to Figure 6 , 7 , 8 and 9 described.

[0133] The image or three-dimensional digital model of the physically manufactured appliance 1030 can be an image, 3D scan data, or other data related to the physical geometry of the manufactured appliance, as discussed herein, and can include, for example, data generated by a scanning or photographic device, such as, for example, CT scans, photography, OCT, and optical scans, as well as post-processing of scans and images. An imaging system can be used to obtain scans or photographs of appliances and other appliances. The scan can be a 3D scan or a 2D photograph representing a projection of a 3D image.

[0134] Prediction model 1040 may be a model of an appliance generated based on a compensation model, such as Fig.11 The developed neural network is shown.

[0135] At box 1130, the model 1010 and the image of the manufactured appliance 1030, depicted as image 1031, are aligned or registered with each other. The image or model can be registered based on, for example, the midline of the dental arch and / or the occlusal surface of the dental arch. Image 1113 shows two models registered with each other. At box 1120, the difference or deviation of the geometry of the physical component 1030 relative to the geometry of the model 1010 is determined. The registration can capture the overall deformation of the appliance, such as shrinkage, bending and twisting of the ends of the dental arch. Based on the model and its registration, other quantities such as chamfers, geometric mismatches of attachment wells and interproximal areas, and thickness distribution can also be captured or measured. The comparison results can be stored in a database for training a neural network.

[0136] Image 1114 shows a displacement graph of the deviation between the physical component and the digital model.

[0137] At block 1150 , geometric features are extracted from the model 1010 , as discussed herein.

[0138] At box 1160, a machine learning or empirical model can be used to correlate the geometric mismatch of the digital model and the physical part. The neural network is trained using the differences or deviations of the model derived from the image 1010 and the data representing the physical part 1030, the extracted features, and the manufacturing settings 1020 as input. This can also or additionally correlate the geometric mismatch and some measurement and production information from the digital model, including local coordinates, local curvature, dentition measurements, printers, manufacturing settings, such as exposure time, power, temperature, etc., as discussed herein. Subsequently, given a new digital model, the model can be used to predict the shape of the produced appliance.

[0139] Voxel- and pixel-based additive manufacturing techniques rely on using discrete voxels or pixels as input to deposit material or deliver energy for the corresponding manufacturing process. Typically, geometric compensation may not translate into physical changes in size because those optimizations may be continuous, while the inputs that achieve the change (e.g., turning on or off voxels used to make a physical model) are typically discrete and may vary, for example, only when the change in compensation changes by at least 50% or enough to cause a voxel or pixel to be printed or not printed. Therefore, changes in voxel or pixel space can also be captured.

[0140] The neural network of other devices that generate the compensation design can introduce a reverse deformation in the digital model of the appliance so that the deviation of the product appliance from the original digital model is less than the deviation that occurred before the compensation. For empirical models, the compensating deformation can be directly calculated backwards from the empirical function generated based on the previously manufactured model.

[0141] For the machine learning model, a reverse learning model is established by using a series of compensating deformations as input to the prediction model and then finding the compensating deformation with the smallest deviation. The compensating deformation with the smallest deviation can then be used to retrain the compensating machine learning model.

[0142] Graph 1115 depicts the neural network correlation of the difference calculation on the Y-axis and the feature extraction on the X-axis for the trained model.

[0143] Return to reference Fig.10 At box 1040, the compensation model (based on machine learning or experience) can be used to generate a compensated 3D model, which is then used as a predictive model for the manufactured part. At box 750, it is determined whether the prediction deviation is acceptable. Various aspects of the model can be evaluated to determine whether the deviation is acceptable. In some embodiments, these aspects include aligner thickness, deviations of expected physical aligner surface locations compared to corresponding locations, and the three-dimensional model. In some embodiments, these aspects include expected physical component geometry compared to expected physical component geometry, such as a geometry defined by the geometry of the three-dimensional digital model of the aligner.

[0144] If the deviation is acceptable, e.g., within a threshold of acceptable deviation, the model or instructions for making the model may be sent to a manufacturing machine for manufacturing at block 1060. In some embodiments, if the deviation is unacceptable, the part or slice thereof may be sent for correction at block 1050 to reduce the prediction deviation at block 1070, where further compensation is applied to the model and the further compensated model is then used at the input to compensate the model and the process repeats itself until an acceptable deviation is reached.

[0145] For example, a compensation model can be used with respect to appliance thickness. The thickness distribution of the appliance in the digital model may be uneven, for example thick at the occlusal surface and thin at the gingival edge. A machine learning model can be trained to associate thickness with measurements, for example, thickness as a function of the position or coordinate (coord) on the appliance, the surface normal direction (z) at coord or the occlusal-buccal component of z, and the local curvature (r) at coord, for example expressed in the form of thickness = f(coord, normal_z, r). Based on this function, compensation in the model can be made, for example, to make the occlusal surface thinner and the bottom edge thicker, so that the printed appliance will have a more uniform thickness distribution. Computing System

[0146] Fig.131310 is a block diagram of an example computing system 1310 capable of implementing one or more embodiments described and / or illustrated herein. For example, all or a portion of the computing system 1310 may be executed alone or in combination with other elements and / or as a means for performing one or more of the steps described herein (such as in Figures 4 to 11 All or a portion of the computing system 1310 may also perform and / or be used as a means for performing any other steps, methods, or processes described and / or illustrated herein.

[0147] Computing system 1310 broadly represents any single-processor or multi-processor computing device or system capable of executing computer-readable instructions. Examples of computing system 1310 include, but are not limited to, a workstation, a laptop computer, a client-side terminal, a server, a distributed computing system, a handheld device, or any other computing system or device. In its most basic configuration, computing system 1310 may include at least one processor 1314 and system memory 1316.

[0148] Processor 1314 generally represents any type or form of physical processing unit (e.g., a hardware-implemented central processing unit) capable of processing data or interpreting and executing instructions. In some embodiments, processor 1314 may receive instructions from a software application or module. These instructions may cause processor 1314 to perform one or more of the functions of the example embodiments described and / or illustrated herein.

[0149] System memory 1316 generally represents any type or form of volatile or non-volatile storage device or medium capable of storing data and / or other computer-readable instructions. Examples of system memory 1316 include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, or any other suitable memory device. Although not required, in some embodiments, computing system 1310 may include a volatile memory unit (e.g., system memory 1316) and a non-volatile storage device (e.g., main storage device 1332, as described in detail below).

[0150] In some examples, system memory 1316 can store and / or load operating system 1340 for execution by processor 1314. In one example, operating system 1340 can include and / or represent software that manages computer hardware and software resources and / or provides common services to computer programs and / or applications on computing system 1310. Examples of operating system 1340 include, but are not limited to, LINUX, JUNOS, MICROSOFT WINDOWS, WINDOWS MOBILE, MAC OS, APPLE's IOS, UNIX, GOOGLE CHROME OS, GOOGLE's ANDROID, SOLARIS, variations of one or more of the above operating systems, and / or any other suitable operating system.

[0151] In some embodiments, the example computing system 1310 may include one or more components or elements in addition to the processor 1314 and the system memory 1316. For example, Fig.13 As shown, computing system 1310 may include memory controller 1318, input / output (I / O) controller 1320, and communication interface 1322, each of which may be interconnected via communication infrastructure 1312. Communication infrastructure 1312 generally represents any type or form of infrastructure capable of facilitating communication between one or more components of a computing device. Examples of communication infrastructure 1312 include, but are not limited to, communication buses (such as Industry Standard Architecture (ISA), Peripheral Component Interconnect (PCI), PCI Express (PCIe), or similar buses) and networks.

[0152] Memory controller 1318 generally represents any type or form of device capable of handling memory or data or controlling communications between one or more components of computing system 1310. For example, in some embodiments, memory controller 1318 may control communications between processor 1314, system memory 1316, and I / O controller 1320 via communications infrastructure 1312.

[0153] I / O controller 1320 generally represents any type or form of module capable of coordinating and / or controlling the input and output functions of a computing device. For example, in some embodiments, I / O controller 1320 may control or facilitate data transfer between one or more elements of computing system 1310, such as processor 1314, system memory 1316, communication interface 1322, display adapter 1326, input interface 1330, and storage interface 1334.

[0154] like Fig.13As shown, computing system 1310 may also include at least one display device 1324 coupled to I / O controller 1320 via display adapter 1326. Display device 1324 generally represents any type or form of device capable of visually displaying information forwarded by display adapter 1326. Similarly, display adapter 1326 generally represents any type or form of device configured to forward graphics, text, and other data from communications infrastructure 1312 (or from a frame buffer, as is known in the art) for display on display device 1324.

[0155] like Fig.13 As shown, the example computing system 1310 may also include at least one input device 1328 coupled to the I / O controller 1320 via an input interface 1330. The input device 1328 generally represents any type or form of input device capable of providing computer or human-generated input to the example computing system 1310. Examples of the input device 1328 include, but are not limited to, a keyboard, a pointing device, a voice recognition device, variations or combinations of one or more thereof, and / or any other input device.

[0156] Additionally or alternatively, the example computing system 1310 may include additional I / O devices. For example, the example computing system 1310 may include an I / O device 1336. In this example, the I / O device 1336 may include and / or represent a user interface that facilitates human interaction with the computing system 1310. Examples of I / O devices 1336 include, but are not limited to, a computer mouse, a keyboard, a monitor, a printer, a modem, a camera, a scanner, a microphone, a touch screen device, variations or combinations of one or more thereof, and / or any other I / O device.

[0157] The communication interface 1322 broadly represents any type or form of communication device or adapter that can facilitate communication between the example computing system 1310 and one or more additional devices. For example, in some embodiments, the communication interface 1322 can facilitate communication between the computing system 1310 and a private or public network including additional computing systems. Examples of the communication interface 1322 include, but are not limited to, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, and any other suitable interface. In at least one embodiment, the communication interface 1322 can provide a direct connection to a remote server via a direct link to a network such as the Internet. The communication interface 1322 can also provide such a connection indirectly through, for example, a local area network (such as an Ethernet), a personal area network, a telephone or cable network, a cellular phone connection, a satellite data connection, or any other suitable connection.

[0158] In some embodiments, communication interface 1322 may also represent a host adapter configured to facilitate communication between computing system 1310 and one or more additional network or storage devices via an external bus or communication channel. Examples of host adapters include, but are not limited to, Small Computer System Interface (SCSI) host adapters, Universal Serial Bus (USB) host adapters, Institute of Electrical and Electronics Engineers (IEEE) 1394 host adapters, Advanced Technology Attachment (ATA), Parallel ATA, and 1394 host adapters. (PATA), Serial ATA (SATA) and external SATA (eSATA) host adapters, Fibre Channel interface adapters, Ethernet adapters, etc. Communication interface 1322 may also allow computing system 1310 to participate in distributed or remote computing. For example, communication interface 1322 may receive instructions from a remote device or send instructions to a remote device for execution.

[0159] In some examples, system memory 1316 can store and / or load network communication program 1338 for execution by processor 1314. In one example, network communication program 1338 can include and / or represent a program that enables computing system 1310 to communicate with another computing system (in Fig.13 1342 and / or software for communicating with another computing system via communication interface 1322. In this example, network communication program 1338 can direct the flow of outgoing traffic sent to other computing systems via network connection 1342. Additionally or alternatively, network communication program 1338 can direct the processing of incoming traffic received from other computing systems via network connection 1342 connected to processor 1314.

[0160] Despite Fig.13 1322, but the network communication program 1338 may alternatively be stored and / or loaded in the communication interface 1322. For example, the network communication program 1338 may include and / or represent at least a portion of software and / or firmware executed by a processor and / or application specific integrated circuit (ASIC) incorporated into the communication interface 1322.

[0161] like Fig.13As shown, the example computing system 1310 may also include a primary storage device 1332 and a backup storage device 1333 coupled to the communication infrastructure 1312 via a storage interface 1334. The storage devices 1332 and 1333 generally represent any type or form of storage device or medium capable of storing data and / or other computer-readable instructions. For example, the storage devices 1332 and 1333 may be a disk drive (e.g., a so-called hard disk drive), a solid-state drive, a floppy disk drive, a tape drive, an optical drive, a flash drive, etc. The storage interface 1334 generally represents any type or form of interface or device for transferring data between the storage devices 1332 and 1333 and other components of the computing system 1310.

[0162] In some embodiments, storage devices 1332 and 1333 may be configured to read from and / or write to a removable storage unit that is configured to store computer software, data, or other computer-readable information. Examples of suitable removable storage units include, but are not limited to, floppy disks, tapes, optical drives, and flash memory devices. Storage devices 1332 and 1333 may also include other similar structures or devices for allowing computer software, data, or other computer-readable instructions to be loaded into computing system 1310. For example, storage devices 1332 and 1333 may be configured to read and write software, data, or other computer-readable information. Storage devices 1332 and 1333 may also be part of computing system 1310, or may be separate devices accessed through other interface systems.

[0163] Many other devices or subsystems may be connected to computing system 1310. Fig.13 All components and devices shown need not be present to practice the embodiments described and / or shown herein. The devices and subsystems referenced above may also be used in conjunction with Fig.13 The computing system 1310 may also be interconnected in different ways as shown. The computing system 1310 may also adopt any number of software, firmware and / or hardware configurations. For example, one or more of the example embodiments disclosed herein may be encoded as a computer program (also referred to as computer software, software application, computer readable instructions or computer control logic) on a computer readable medium.

[0164] The term "computer-readable medium" as used herein generally refers to any form of device, carrier or medium capable of storing or executing computer-readable instructions. Examples of computer-readable media include, but are not limited to, transmission-type media such as carrier waves, and non-transitory media such as magnetic storage media (e.g., hard disk drives, tape drives, and floppy disks), optical storage media (e.g., compact disks (CDs), digital video disks (DVDs), and Blu-ray (BLU-RAY) disks), electronic storage media (e.g., solid-state drives and flash memory media), and other distribution systems.

[0165] A computer-readable medium containing a computer program may be loaded into computing system 1310. All or a portion of the computer program stored on the computer-readable medium may then be stored in system memory 1316 and / or various portions of storage devices 1332 and 1333. When executed by processor 1314, the computer program loaded into computing system 1310 may cause processor 1314 to perform and / or serve as a means for performing the functions of one or more of the example embodiments described and / or illustrated herein. Additionally or alternatively, one or more of the example embodiments described and / or illustrated herein may be implemented in firmware and / or hardware. For example, computing system 1310 may be configured as an application specific integrated circuit (ASIC) suitable for implementing one or more of the example embodiments disclosed herein.

[0166] 14 is a block diagram of an example network architecture 1400, in which client systems 1410, 1420, and 1430 and servers 1440 and 1445 can be coupled to a network 1450. As detailed above, all or a portion of the network architecture 1400 can perform and / or serve as a means for performing one or more of the steps disclosed herein, either alone or in combination with other elements (e.g., Figures 4 to 11 All or a portion of the network architecture 1400 may also be used to perform and / or be a means for performing other steps and features set forth in the present disclosure.

[0167] Client systems 1410, 1420, and 1430 generally represent any type or form of computing device or system, such as Fig.13 1410, 1420, and / or 1430 and / or servers 1440 and / or 1445 may include Figure 5 All or a portion of system 500 in.

[0168] As shown in FIG. 14 , one or more storage devices 1460(1)-(N) may be directly attached to server 1440. Similarly, one or more storage devices 1470(1)-(N) may be directly attached to server 1445. Storage devices 1460(1)-(N) and storage devices 1470(1)-(N) generally represent any type or form of storage device or medium capable of storing data and / or other computer-readable instructions. In some embodiments, storage devices 1460(1)-(N) and storage devices 1470(1)-(N) may represent network-attached storage (NAS) devices configured to communicate with servers 1440 and 1445 using various protocols such as Network File System (NFS), Server Message Block (SMB), or Common Internet File System (CIFS).

[0169] The servers 1440 and 1445 may also be connected to a storage area network (SAN) fabric 1480. The SAN fabric 1480 generally represents any type or form of computer network or architecture capable of facilitating communication between multiple storage devices. The SAN fabric 1480 may facilitate communication between the servers 1440 and 1445 and multiple storage devices 1490(1)-(N) and / or smart storage array 1495. The SAN fabric 1480 may also facilitate communication between the client systems 1410, 1420, and 1430 and the storage devices 1490(1)-(N) and / or smart storage array 1495 via the network 1450 and the servers 1440 and 1445, such that the devices 1490(1)-(N) and array 1495 appear to be locally attached to the client systems 1410, 1420, and 1430. As with storage devices 1460(1)-(N) and storage devices 1470(1)-(N), storage devices 1490(1)-(N) and smart storage array 1495 generally represent any type or form of storage device or medium capable of storing data and / or other computer-readable instructions.

[0170] In certain embodiments, and with reference to Fig.13 An example computing system 1310 such as Fig.13The communication interface 1322 in FIG. 14 may be used to provide connectivity between each of the client systems 1410, 1420, and 1430 and the network 1450. The client systems 1410, 1420, and 1430 may be able to access information on the server 1440 or 1445 using, for example, a web browser or other client software. Such software may allow the client systems 1410, 1420, and 1430 to access data hosted by the server 1440, server 1445, storage devices 1460(1)-(N), storage devices 1470(1)-(N), storage devices 1490(1)-(N), or smart storage array 1495. Although FIG. 14 depicts the use of a network, such as the Internet, to exchange data, the embodiments described and / or illustrated herein are not limited to the Internet or any particular network-based environment.

[0171] In at least one embodiment, all or part of one or more of the exemplary embodiments disclosed herein may be encoded as a computer program and loaded onto and executed by server 1440, server 1445, storage devices 1460(1)-(N), storage devices 1470(1)-(N), storage devices 1490(1)-(N), smart storage array 1495, or any combination thereof. All or part of one or more of the exemplary embodiments disclosed herein may also be encoded as a computer program that is stored in server 1440, executed by server 1445, and distributed to client systems 1410, 1420, and 1430 via network 1450.

[0172] As detailed above, one or more components of the computing system 1310 and / or the network architecture 1400 may be executed alone or in combination with other elements and / or as a means for performing one or more steps of the example methods for virtual care.

[0173] Fig.14A , 14B and 14C depict occlusal stability features, such as bite blocks or bite ramps, generated using a thickness map. Fig.14A An example of a bite block 1411 and corresponding bite block receiving cavity 1416 that can help stabilize a patient's bite when using an orthodontic appliance is shown. The patient's natural bite in the bite is determined by the position and orientation of the patient's teeth and how the teeth of the lower jaw interact with the teeth of the upper jaw and the structure of the temporomandibular joint (also known as the TMJ joint).

[0174] The orthodontic appliance has a thickness that changes the way the patient's upper and lower jaw teeth interact in bite. The thickness can change the way the patient's upper and lower jaws interact and cause discomfort to the patient. In some embodiments, changes in the patient's bite may cause changes in the patient's TMJ joint. To address the possibility of patient discomfort, the occlusal surface of the orthodontic appliance can be changed to promote a stable bite and improve patient comfort.

[0175] In some embodiments, a set of generated models of orthodontic appliances can be modified to include a bite block 1411 and a corresponding bite block receiving cavity 1416, which can help stabilize the patient's bite when using the orthodontic appliance. The bite block 1411 can be a structure extending from the occlusal surface of the appliance 1402, such as extending from the upper appliance of a set of orthodontic appliances. The bite block 1410 can be generated by changing the thickness map of the orthodontic appliance 1402. Fig.15 Discuss the appliance thickness chart in more detail.

[0176] In some embodiments, the bite block 1411 can be a bite ramp. The bite ramp can include an inclined surface 1414, wherein the thickness map of the appliance changes relative to the position on the appliance. For example, to form a Fig.14A 14. In some embodiments, the transition from a slight thickness change to no thickness change to a maximum thickness change can be linear, such that a ramp 1414 is formed on the occlusal surface of the appliance 1402. In some embodiments, a stepped shape, such as step shape 1412, is formed at the end of the occlusal ramp, where the thickness of the appliance changes rapidly from the maximum value of the occlusal ramp height back to the thickness of the originally generated appliance. The change can be a step change. In some embodiments, the change can be at a steeper or greater slope than the slope of ramp 1414.

[0177] In some embodiments, a bite block receiving cavity 1416 can be formed in an opposing appliance 1404 in a set of appliances. The bite block receiving cavity can include a ramp that corresponds to ramp 1414, wherein a change in the thickness profile of the appliance changes relative to a position on the appliance. For example, to form a ramp in the bite block receiving cavity 1416, such as Fig.14AAs shown, the more posterior position of the appliance changes with a smaller reduction in thickness, while the more anterior position changes with a reduction in thickness. In some embodiments, the transition from a slight thickness change to no thickness change to a maximum thickness change can be linear, so that the slope of the inclined surface of the bite block receiving cavity 1416 matches the slope of the inclined surface 1414. In some embodiments, a shape such as a step shape is formed at the end of the bite bevel, where the thickness of the appliance quickly changes from the maximum reduction in the height of the bite bevel receiving cavity back to the original generated thickness of the appliance. The change can be a step change or a smooth change. In some embodiments, the change can be at a steeper or greater slope than the slope of the inclined surface of the bite block receiving cavity. In some embodiments, the shape of the bite block receiving cavity corresponds to the shape of the bite block 1411, so that the bite block 1411 is nested with the bite block receiving cavity 1416.

[0178] The thickness of the appliance in the bite block receiving cavity may be reduced to zero, thereby forming a hole in the appliance.

[0179] In some embodiments, the thickness of an appliance in the form of a bite block may be determined based on a simulation of the patient's jaws in occlusion. For example, a simulation may be used to determine the contact between the maxilla and mandible during each stage of the orthodontic treatment, and a bite block may be generated for each stage of the orthodontic treatment to stabilize the patient's bite. In some embodiments, the position, size, shape, and other features of the bite block and the bite block receiving cavity may be varied at each stage of treatment to facilitate a stable bite for the patient.

[0180] Fig. 14B An example of thickness map changes is shown to provide a more comfortable and natural bite for the patient. Fig. 14B The upper and lower front teeth, such as the central incisors, are shown in bite while wearing the modified orthodontic appliances 1402, 1404. In such an embodiment, the initial thickness of the appliances 1402, 1404 may be such that the natural bite between the patient's teeth would be uncomfortable. Therefore, the thickness map of the appliances 1402, 1404 near the bite between the patient's upper and lower appliances 1402, 1404 may be changed to provide a more natural bite.

[0181] Although the reference Fig.14A and Fig. 14C The variations in thickness maps discussed form bite blocks and corresponding bite block receiving cavities, but in some embodiments, such as in the occlusion of the incisors and other anterior teeth or incisor service, the thickness map can be modified by reducing the thickness of the upper and lower appliances to provide a tighter bite between the patient's teeth and jaws.

[0182] Reference Fig. 14BIn some embodiments, a model of a set of generated orthodontic appliances can be modified to include a first reduced thickness portion 1432 and a corresponding second reduced thickness portion 1432, which can help stabilize the patient's bite and provide a more natural, tighter bite when wearing the orthodontic appliances. The first reduced thickness portion 1432 can be part of an appliance 1402, such as an upper appliance of a set of orthodontic appliances. The first reduced thickness portion 1432 can be generated by changing the thickness map of the orthodontic appliance 1404. Fig.15 Discuss the appliance thickness chart in more detail.

[0183] In some embodiments, the first reduced thickness portion 1432 can be a reduced surface thickness, wherein changes to the thickness map of the appliance are changed relative to the location on the appliance. The first reduced thickness portion 1432 can include three portions: a first central portion 1444, a second portion 1442 on the lingual side 1422 of the first portion 1444, and a third portion 1446 on the buccal side 1421 of the central portion 1444.

[0184] In some embodiments, the second or lingual portion 1442 and the third or buccal portion 1456 can be transition areas that transition the thickness from the reduced thickness or minimum thickness within the first region 1444 to the initial generated thickness of the appliance 1402 outside the first reduced thickness portion 1432. The thickness profile of the first central portion 1444 can be reduced to a first minimum thickness. The thickness of the first central portion 1444 can be a constant thickness that follows the contour of the tooth receiving cavity or the interior surface of the appliance at the tooth location. In some embodiments, the total desired distance between the upper and lower teeth can be determined or set. The minimum thickness of the appliance at the first central portion 1444 can be half of the minimum distance between the upper and lower teeth. In some embodiments, the thickness profile of the first central portion 1444 can be selected to maintain the desired bite between the mandible and the maxilla and adjusted to match or fit, such as nestingly fitting with the shape of the appliance 1404 or the teeth of the opposing jaw.

[0185] In some embodiments, the second portion or lingual portion 1442 can extend from a location of a previously generated appliance thickness on the lingual side of the first central portion 1444 to the first central portion 1444. The thickness profile of the second portion or lingual portion 1442 can be a first minimum thickness at the interface between the first central portion 1444 and the second portion or lingual portion 1442. The thickness profile of the second portion or lingual portion 1442 can be a first maximum thickness at the interface between the first central portion 1444 and the previously generated appliance thickness location. The thickness of the second portion or lingual portion 1442 can be a variable thickness that follows the contour of the outer surface shape of the portion 1452 of the relative appliance. The thickness of the second portion or lingual portion 1442 can be a variable thickness that changes linearly from a thickness at a previously generated appliance thickness and a thickness at the interface between the first central portion 1444 and the second portion or lingual portion 1442. In some embodiments, the thickness profile of the first central portion 1444 and the second portion or lingual portion 1442 can be selected to maintain a desired bite between the mandible and the maxilla and adjusted to match or mate with the shape of portion 1431 of the appliance 1404 or the teeth of the opposing jaw, such as nestedly fitting so that the shape of portion 1431 matches the shape of portion 1432 to allow the surfaces to mate with each other.

[0186] In some embodiments, the third portion or buccal portion 1456 can extend from a location of a previously generated thickness of the appliance on the lingual side of the first central portion 1444 to the first central portion 1444. The thickness map of the second portion or lingual portion 1442 can be a first minimum thickness at the interface between the first central portion 1444 and the second portion or lingual portion 1442. The thickness map of the second portion or lingual portion 1442 can be a first maximum thickness at the interface between the first central portion 1444 and the previously generated appliance thickness location. The thickness of the second portion or lingual portion 1442 can be a variable thickness that follows the contour of the outer surface shape of the portion 1431 of the relative appliance. The thickness of the second portion or lingual portion 1442 can be a variable thickness that changes linearly from the thickness at the previously generated appliance thickness and the thickness at the interface between the first central portion 1444 and the second portion or lingual portion 1442. In some embodiments, the thickness profile of the first central portion 1444 and the second portion or lingual portion 1442 can be selected to maintain a desired bite between the mandible and the maxilla and adjusted to match or fit, such as nesting tightly with the shape of portion 1452 of the appliance 1404 or the teeth of the opposing jaw such that the shape of portion 1431 matches the shape of portion 1432 to allow the surfaces to mate with each other.

[0187] In some embodiments, the thickness profile of the corresponding second reduced thickness 1431 of the appliance 1404 can help stabilize the patient's bite and provide a more natural, tighter bite when wearing the orthodontic appliance. The second reduced thickness portion 1431 can be a portion of the appliance 1404, such as a lower appliance in an orthodontic appliance set. The second reduced thickness portion 1431 can be generated by changing the thickness profile of the orthodontic appliance 1404. Fig.15 Discuss the appliance thickness chart in more detail.

[0188] In some embodiments, the second reduced thickness portion 1432 can be a reduced surface thickness, wherein the change to the thickness map of the appliance changes relative to the location on the appliance. The first reduced thickness portion 1431 can include three portions: a first central portion 1454, a second portion 1452 located on the lingual side 1426 of the first portion 1454, and a third portion 1456 located on the buccal side of the central portion 1454.

[0189] In some embodiments, the second portion or lingual portion 1452 and the third portion or buccal portion 1456 can be transition areas that transition the thickness from the reduced thickness or minimum thickness within the first region 1454 to the previously generated thickness of the appliance 1404 outside the first reduced thickness portion 1456. The thickness map of the first central portion 1454 can be reduced to a first minimum thickness. The thickness of the first central portion 1454 can be a constant thickness that follows the contour of the tooth receiving cavity or the interior surface of the appliance at that tooth location. In some embodiments, the total desired distance between the upper and lower teeth can be determined or set. The minimum thickness of the appliance at the first central portion 1454 can be half of the minimum distance between the upper and lower teeth. In some embodiments, the thickness map of the first central portion 1454 can be selected to maintain the desired bite between the mandible and the maxilla and adjusted to match or fit, such as nestedly matching the shape of the appliance 1402 or the teeth of the opposing jaw.

[0190] In some embodiments, the second portion or lingual portion 1452 can extend from a location of a previously generated thickness of the appliance on the lingual side of the first central portion 1454 to the first central portion 1454. The thickness profile of the second portion or lingual portion 1452 can be a first minimum thickness at the interface between the first central portion 1454 and the second portion or lingual portion 1452. The thickness profile of the second portion or lingual portion 1452 can be a first maximum thickness at the interface between the first central portion 1454 and the location of the previously generated thickness of the appliance. The thickness of the second portion or lingual portion 1452 can be a variable thickness that follows a contour of an outer surface shape of the portion 1442 of the relative appliance. The thickness of the second portion or lingual portion 1452 can be a variable thickness that changes linearly from a thickness at a previously generated thickness of the appliance and a thickness at an interface between the first central portion 1454 and the second portion or lingual portion 1452. In some embodiments, the thickness profile of the first central portion 1454 and the second portion or lingual portion 1452 can be selected to maintain a desired bite between the mandible and the maxilla and adjusted to match or engage with the shape of portion 1432 of the appliance 1402 or the teeth of the opposing jaw, such as to fit nestedly.

[0191] In some embodiments, the third portion or buccal portion 1456 can extend from the location of the previously generated thickness of the appliance on the lingual side of the first central portion 1454 to the first central portion 1454. The thickness profile of the second portion or lingual portion 1452 can be a first minimum thickness at the interface between the first central portion 1454 and the second portion or lingual portion 1452. The thickness profile of the second portion or lingual portion 1452 can be a first maximum thickness at the interface between the first central portion 1454 and the location of the previously generated thickness of the appliance. The thickness of the second portion or lingual portion 1452 can be a variable thickness that follows the contour of the outer surface shape of the portion 1432 of the relative appliance. The thickness of the second portion or lingual portion 1452 can be a variable thickness that changes linearly from the thickness at the previously generated thickness of the appliance and the thickness at the interface between the first central portion 1454 and the second portion or lingual portion 1452. In some embodiments, the thickness profile of the first central portion 1454 and the second portion or lingual portion 1452 can be selected to maintain a desired bite between the mandible and the maxilla and adjusted to match or fit with the shape of portion 1452 of the appliance 1402 or the teeth of the opposing jaw, such as to fit in a nested manner.

[0192] In some embodiments, the physician may prefer to provide some disocclusion between the patient's upper and lower jaws. In some embodiments, such as during tooth eruption or extraction, where a tooth is pulled out of the gums or removed to adjust its height, contact between the patient's upper and lower jaws may inhibit an increase in tooth height or inhibit the eruption of a tooth. In such embodiments, disocclusion may help reduce or eliminate bite forces at the location of the increased height tooth.

[0193] The patient's natural bite in the bite is determined by the position and orientation of the patient's teeth and how the teeth of the lower jaw interact with the teeth of the upper jaw and the structure of the temporomandibular joint (also known as TMJ). In some embodiments, the isolation of the work can help change the structure of the patient's TMJ in order to change the patient's bite.

[0194] Fig. 14C An example of a bite block 1433 and corresponding bite block receiving cavity 1436 that can assist in deocclusion of a patient's jaws and stabilize the patient's bite when using an orthodontic appliance is shown.

[0195] In some embodiments, the model of a set of generated orthodontic appliances can be modified to include a bite block 1433 and a corresponding bite block receiving cavity 1436 that can help the patient's jaws to be free of bite and stabilize the patient's bite when using the orthodontic appliances. The bite block 1433 can be a structure extending from the occlusal surface of the appliance 1402, such as an upper appliance of a set of orthodontic appliances. The bite block 1433 can be generated by changing the thickness map of the orthodontic appliance 1402. Fig.15 Discuss the appliance thickness chart in more detail.

[0196] In some embodiments, the bite block 1433 can be a bite ramp. The bite ramp can include an inclined surface 1434, wherein the change in the thickness map of the aligner changes relative to the position on the aligner. For example, to form a Fig. 14C 1434. In some embodiments, the transition from a slight thickness change to no thickness change to a maximum thickness change can be linear, such that a ramp 1434 is formed on the occlusal surface of the appliance 1402. In some embodiments, a stepped shape, such as step shape 1432, is formed at the end of the occlusal ramp, where the thickness of the appliance changes rapidly from the maximum value of the occlusal ramp height back to the thickness of the originally generated appliance. The change can be a step change. In some embodiments, the change can present a steeper or greater slope than the slope of ramp 1434.

[0197] In some embodiments, a bite block receiving cavity 1436 can be formed in an opposing appliance 1404 of a set of appliances. The bite block receiving cavity can include an inclined surface that corresponds to the inclined surface 1434, wherein changes in the appliance thickness map change relative to the position on the appliance. For example, to form an inclined surface in the bite block receiving cavity 1436, such as Fig. 14C As shown, the more posterior position of the appliance changes with a smaller decrease in thickness, while the more anterior position of the appliance changes with a larger decrease in thickness. In some embodiments, the transition from a small change in thickness to no change to a maximum change in thickness can be linear, so that the slope of the ramp of the bite block receiving cavity 1436 matches the slope of the ramp 1434. In some embodiments, a stepped shape, such as a staircase shape, is formed at the end of the bite ramp, where the thickness of the appliance changes rapidly from the maximum decrease in the bite ramp receiving cavity height back to the thickness of the originally generated appliance. The change can be a step change. In some embodiments, the change can present a steeper or larger slope than the slope of the ramp of the bite block receiving cavity. In some embodiments, the shape of the bite block receiving cavity corresponds to the shape of the bite block 1433, so that the bite block 1433 fits nested with the bite block receiving cavity 1436.

[0198] In some embodiments, additional height 1438 may be added to the bite block receiving cavity 1436 or the bite block 1434. The additional height 1438 may be a fixed height to induce an occlusion of the patient's jaws. For example, if the dentist requires a 1 mm occlusion between the upper and lower jaws, a thickness of 1 mm may be added to the thickness map at the bite block receiving cavity 1438. The total change in the thickness map may be the sum of the thickness added to provide the occlusion and the thickness subtracted to provide the bite block receiving cavity 1436. Similarly, if additional height 1438 is added to the bite block 1434, the additional height 1438 may be the sum of the height added to provide a de-occlusion and the height added to form the bite block or bite ramp.

[0199] Fig.15A thickness map 1500 of an appliance is depicted. A thickness map can be a map of locations on an appliance and the corresponding thickness of the appliance at those locations. In some embodiments, the appliance can be generated as a three-dimensional model of a solid component having the actual appliance geometry, which already contains thickness information, such as a solid 3D digital model. A three-dimensional model of a solid component having the actual appliance geometry is generated, and a change in thickness can be a change in the thickness of the solid component, such as a change or movement of an outer surface of the three-dimensional model of the solid component having the actual appliance geometry to change the thickness of the appliance. Throughout this disclosure, reference can be made to modifications to the solid model rather than to modifications to the thickness map. In some embodiments, a thickness map such as thickness map 1500 can be a two-dimensional shell mesh or a mesh of shell elements and a corresponding thickness map for each element or each node at a three-dimensional location in space. In some embodiments, each element corresponds to a location on the appliance. The thickness can be a thickness value corresponding to the appliance at that node or element. In some embodiments, the two-dimensional shell mesh or mesh of shell elements and the corresponding thickness map for each element or each node at a three-dimensional position in space can be a two-dimensional shell mesh or mesh of shell elements representing the shape of an inner surface of the appliance, such as a tooth-facing surface of the appliance. The thickness can be a thickness originating from the inner surface.

[0200] In some embodiments, the thickness can be a thickness centered on the location of the element, wherein half of the thickness is on one side of the element, such as in a direction away from the appliance for a tooth receiving cavity defined by the appliance, and half of the thickness is on the other side of the element, such as in a direction toward or into the tooth receiving cavity defined by the appliance. In some embodiments, the thickness at a location or element can be both the thickness of the shell element location and the displacement of the shell element location. For example, in some embodiments, the thickness of the appliance at a location can be displaced from the three-dimensional location in space of the shell element or the location of the appliance. In such embodiments, the displacement can provide additional gaps or spaces between the teeth and the inner surface of the appliance when the patient wears the appliance, or the displacement can provide a reduction in the gaps or spaces between the teeth and the inner surface of the appliance when the patient wears the appliance.

[0201] As discussed herein, the thickness map 1500 of the appliance can be adjusted in a variety of ways. For example, when the patient wears the appliance, the occlusal map of the occlusal surface 1502 of the appliance can be adjusted or modified to provide more or less space between the occlusal surfaces of the patient's teeth and the appliance, e.g., as described with respect to Fig.16In some embodiments, the biting surface 1502 can be adjusted or modified to provide a bite block or bite ramp on the biting surface of the patient appliance and the corresponding bite block or bite block receiving cavity to adjust the patient's bite or provide a comfortable and stable patient bite for the patient during orthodontic treatment.

[0202] In some embodiments, the thickness map 1500 of the appliance can be adjusted at the incisor positions 1510, 1512, which can be the lingual position 1510 and / or the buccal position 1512. The thickness map can be adjusted at the incisor positions 1510, 1512 to provide an improved bite between the patient's upper and lower jaws, for example, as described with respect to Fig. 14B As shown and described.

[0203] In some embodiments, the thickness map 1500 of the appliance can be adjusted at an occlusal location adjacent to an interproximal region between two adjacent teeth. For example, the thickness map can be adjusted at a buccal location 1522 of the interproximal location between two adjacent teeth and at a lingual location 1520 of the interproximal location between two adjacent teeth. The thickness map 1500 can be adjusted at the interproximal locations 1520, 1522 to adjust the stiffness of the appliance in the occlusal and interproximal regions to provide better locking of the appliance to the patient's teeth, such as to better retain the appliance on the dentition, to provide better attachment to anchor teeth or non-moving teeth, to adjust the activation energy to move teeth, or to promote or hinder rotation of teeth, as described herein with respect to Fig.16 , 17A and as described in 17B.

[0204] Fig.16 A cross section of the occlusal portion of an appliance generated using a thickness map for intruding or extruding teeth on corresponding teeth of a patient is described. Fig.16 In the embodiment shown, tooth 1602 is being intruded into the patient's jaw, while tooth 1604 may be extruded from the patient's jaw. The thickness maps 1610, 1612, 1614 may be adjusted to provide more intrusion, less contact or force on the teeth, or to provide stiffness to the appliance.

[0205] The tooth 1602 may intrude into the patient's jaw due to its protrusion across the occlusal plane of the patient's jaw and cause premature contact with the patient's opposing jaw. The occlusal surface of the appliance may be thickened at a location 1610 corresponding to the occlusal surface of the appliance above the occlusal surface of the patient's tooth 1602. Thickening the occlusal surface of the appliance above the patient's tooth 1602 may provide a greater active intrusive force on the tooth. The force applied to the tooth may be a function of many variables, such as the local stiffness of the appliance, which may be affected by the thickness of the appliance, the displacement of the surface of the appliance at the tooth, such as how much the appliance deforms when the appliance contacts the tooth, and other factors. Increasing the thickness of the appliance at location 1610 may increase the local stiffness of the appliance near the tooth 1602. Thickening the appliance in a direction away from the tooth may increase the local stiffness of the appliance near the tooth 1602 without increasing the deformation of the appliance at a location near the tooth. Thickening the appliance in a direction toward the teeth may increase the deformation of the appliance when it is placed on the patient's teeth, and therefore increase the forces on the patient's teeth.

[0206] The tooth 1604 may be extruded from the patient's jaw because it is an erupting permanent tooth that replaces a deciduous tooth (or baby tooth). The occlusal surface of the appliance may be thinned at a location 1612 that corresponds to the occlusal surface of the appliance above the occlusal surface of the patient's tooth 1604. Thinning the occlusal surface of the appliance above the patient's tooth 1604 may provide space for the tooth to extrude and may also reduce the force on the tooth 1604 compared to a standard or previously generated thickness of the appliance. As discussed herein, the force applied to the tooth may be a function of many variables, such as the local stiffness of the appliance, which may be affected by the thickness of the appliance, the surface displacement of the appliance at the tooth, such as how much the appliance deforms when the appliance contacts the tooth, and other factors. Reducing the thickness of the braces at a position 1612 that is positionally offset from the position of the braces or the position of a housing element in a direction away from the tooth 1604 or the tooth receiving cavity that receives the tooth 1604 can reduce the local stiffness of the braces near the tooth 1604 and provide space for erupting teeth within the tooth receiving cavity.

[0207] In some embodiments, the occlusal surfaces adjacent to an erupting, extruding, or intruding tooth may be thickened or thinned to adjust the distribution of intrusive forces, provide space for the erupting tooth, and / or reduce the forces that may be applied to the erupting tooth.

[0208] Fig.17A and Fig. 17BA cross section of the occlusal and interproximal portions of the appliance 1700 generated using a thickness map and a model of the interproximal forces applied by the appliance 1700 is depicted. The thickness maps of the occlusal interproximal locations 1712, 1714 can be changed to adjust the thickness of the occlusal interproximal locations, thereby changing the function of the appliance. For example, the thickness of the occlusal interproximal locations can be increased to help lock the active teeth to provide better appliance retention and tooth retention on other teeth of the appliance. In some embodiments, the thickness of the occlusal interproximal portion of the appliance can be thinned to reduce the activation energy of the appliance and provide easier movement of the patient's teeth 1702. In some embodiments, the occlusal interproximal locations can be thickened and thinned asymmetrically relative to the buccal and lingual sides in order to increase or decrease the rotational forces on the patient's teeth.

[0209] The change in thickness of the appliance can be represented by the change in the stiffness of the appliance. The stiffness can be represented by springs 1720, 1722, and also represented as K1 to K8. A higher stiffness represents a harder position on the appliance, while a lower stiffness represents a less rigid position, such as a flexible position on the appliance.

[0210] In some embodiments, in order to lock the tooth 1702 to the appliance, the interproximal positions 1712 and 1714 can be thickened on both the occlusal and buccal sides. The interproximal positions 1712, 1714 on the occlusal and buccal sides of the teeth between the thickened tooth 1702 and the adjacent anterior teeth 1704 and between the tooth 1702 and the adjacent posterior teeth 1706 can be used to lock the tooth 1702. Non-active teeth can be teeth that are not intended to move during a specific treatment stage. In some embodiments, non-active teeth can be considered anchor teeth. Locking the appliance around the anchor teeth can provide better retention of the appliance as a whole and facilitate more reliable force transmission to the neighbors. Providing better appliance retention for active teeth (such as teeth that move during the treatment stage) can allow the appliance to provide more predictable movement forces on the teeth, and can also prevent the appliance from accidentally falling off the patient's teeth.

[0211] In some embodiments, the higher flexibility and / or reduced stiffness of the appliance can reduce the activation energy of the appliance and reduce the forces applied to the teeth. The activation energy can be considered as the energy that moves the teeth due to the deflection of the appliance onto the dentition. By selectively reducing the activation energy of the appliance, greater overall retention can be achieved by reducing the deformation of the appliance compared to the original thickness, which also helps to reduce the detachment of the appliance from the teeth.

[0212] For example, by reducing the thickness of the appliance at the interproximal location 1712, the activation energy of the appliance between teeth 1706 and 1702 can be reduced. Similarly, by thinning the activation area at the interproximal location 1714, the activation energy of the appliance between teeth 1702 and 1704 can be reduced.

[0213] In some embodiments, it may be desirable to increase or decrease the thickness in the occlusal interproximal region in order to facilitate or hinder positioning of the teeth. For example, thickening the occlusal interproximal region 1712 on the lingual side (represented by spring K3) and the occlusal interproximal region 1714 on the buccal side (represented by spring K6), while reducing or thinning the occlusal interproximal region 1712 on the buccal side (represented by spring K4) and the occlusal interproximal region 1714 on the lingual side (represented by spring K5) can facilitate counterclockwise rotation of the tooth 1702, and can hinder or resist clockwise rotation of the tooth 1702.

[0214] In some embodiments, thinning the occlusal interproximal area 1712 on the lingual side (represented by spring K3) and the occlusal interproximal area 1714 on the buccal side (represented by spring K6), while thickening the occlusal interproximal area 1712 on the buccal side (represented by spring K4) and the occlusal interproximal area 1714 on the lingual side (represented by spring K5), can promote the clockwise rotation of the tooth 1702, and can hinder or resist the counterclockwise rotation of the tooth 1702.

[0215] Fig.18 A method 1800 of generating and adjusting a force distribution and generating a thickness map is depicted.

[0216] At block 1810, a target tooth movement is determined. The tooth movement may be determined based on a treatment plan or a stage of a treatment plan. The treatment plan may be based on information about Figure 4 and the processes shown and described elsewhere herein. In some embodiments, the target motion may be a motion that modifies a tooth in a treatment plan or a modified motion of a stage of a treatment plan.

[0217] At box 1830, a simulation is performed to calculate forces and optimize the appliance shape for the target tooth movement. The simulation can include a finite element model of both the patient's anatomy (including teeth, gums, jaws, and other anatomical structures) and clinical data, and the appliance can be used to simulate the movement of the teeth. Using the finite element model and the target movement, which can include a direction and distance or a rotational direction and a rotational distance or angle, the simulation can determine modifications to the thickness map of the appliance to optimize the force system for the desired movement of the teeth. In some embodiments, the simulation can determine the desired thickness map to improve the movement of the teeth by improving the force system, such as increasing the movement of both during the treatment phase.

[0218] In some embodiments, the input to the simulation may also include an indication of the teeth and the type of movement. The simulation may use the indicated teeth and the type of movement to simulate appropriate changes to the thickness map, such as changing the thickness of the interproximal occlusal surfaces to reduce the activation energy of the appliance, increase or decrease rotation through asymmetric stiffness changes, or improve locking of the teeth and provide improved retention of the appliance, such as with respect to Fig.17A and Fig. 17B discussed.

[0219] In some embodiments, the simulation may determine changes in the thickness of the occlusal surface to improve the stability and comfort of the patient's jaw in the occlusion, such as with respect to Fig.14A , 14B and as shown and described in 14C.

[0220] In some embodiments, the simulation may determine changes in the thickness of the occlusal surface to improve extrusion or intrusion of one or more teeth of the patient, such as with respect to Fig.16 As shown and described.

[0221] Full simulations such as using finite element models and clinical data can be time consuming when used to generate thickness maps for each patient and potentially for each stage of treatment planning for each patient. In some embodiments, a surrogate model for moving teeth can be used to generate a modified thickness map of an appliance to affect the movement of the patient's teeth.

[0222] At box 1820, a surrogate model for moving teeth based on a complete simulation can be used to determine forces and appliance shapes to affect tooth movement. The surrogate model for simulating tooth movement can be based on one or more complete finite element models discussed with respect to box 1830. The surrogate model can be a simplified model of the appliance and the patient's anatomical system. The surrogate model can be an optimization and simplification of the finite element model. The surrogate model can simulate the behavior of the simulation while being evaluated at a lower computational cost. The surrogate model can be generated based on data derived from the finite element model, which is based on modeling the response of the finite element model to a finite number of data points (such as a finite number of forces and directions). In some embodiments, a response surface method can be used to generate a surrogate model to generate a polynomial model that approximates the behavior of the finite element model. Other surrogate model types can include kriging, a more generalized Bayesian method, gradient-enhanced kriging (GEK), radial basis functions, support vector machines, spatial mapping, artificial neural networks, and Bayesian networks.

[0223] At block 1840, a desired thickness map is generated based on the model. The desired thickness map may be an output of the simulation or modeling of blocks 1820, 1830. The modified thickness map may be modified as described above with respect to FIGS. 14-17.

[0224] Fig.19A A de-occluded patient jaw is depicted. In some embodiments, the bite thickness map may be modified to control the articulation of the jaw to improve comfort or use an appliance to de-occlude the jaw to address articulation issues and the patient. The patient's mandible 1914 may be de-occluded from the patient's maxilla 1912 based on a desired distance 1916, 1918 and / or an angle 1920 between the mandible 1914 and the maxilla 1912.

[0225] De-occluding the patient's lower jaw 1914 from the patient's upper jaw 1912 may include generating a thickness map that extends the occlusal surface of the patient's upper or lower appliance so as to set the patient's jaw at a desired distance 1916, 1918 and / or angle 1920 in occlusion. One or more portions of the occlusal surface may have an increased thickness. In some embodiments, the forces caused by the patient's chart in occlusion due to the increased occlusal thickness may cause undesirable forces on the patient's teeth, which may inhibit or alter the movement of the patient's teeth. In some embodiments, the location of the increased occlusal thickness may be determined so that the forces applied to those locations of the occlusal surface are distributed in a manner that reduces the undesirable forces on the patient's teeth. For example, increased occlusal forces at locations where teeth are extruded or erupted may cause undesirable intrusive forces on the erupted or extruded teeth.

[0226] In some embodiments, the location of the increased bite pressure may cause discomfort to the patient. The thickness map of the patient's bite service can be adjusted to provide a more uniform pressure across the patient's teeth. For example, the pressure on any tooth can be no more than 30% greater than the pressure on any other tooth subjected to the bite force generated by the patient's jaw de-occlusion. In some embodiments, the disclosed quantities provided by the modification of the thickness map and generated by the simulation can provide tolerances for manufacturing errors and tooth movement. In some embodiments, the thickness map can include thicknesses at locations or elements on the occlusal surface that do not exceed half of the desired distance between the upper and lower occlusal surfaces of the patient's jaw.

[0227] Fig.19B A method 1900 for generating a thickness map for de-occluding a patient's jaw is described. At block 1902, a target occlusion in the occlusion is determined. The target occlusion may be a target distance between points on the occlusal service of the patient's dental arch and / or a target angle between the upper and lower dental arches. The target occlusion is then used as an input at block 1904.

[0228] At box 1904, a desired thickness map is determined using a surrogate model for achieving a target occlusion in occlusion. A surrogate model for achieving a target occlusion in occlusion that can be based on a full simulation can be used to determine an occlusal surface thickness map to achieve the target occlusion. A surrogate model for simulating an occlusal surface to achieve a target occlusion can be based on one or more full finite element models. The surrogate model can be a simplified model of the appliance and the patient's anatomical system. The surrogate model can be an optimization and simplification of the finite element model. The surrogate model can simulate the behavior of the simulation while being evaluated at a lower computational cost. The surrogate model can be generated based on data derived from the finite element model, which is based on modeling the response of the finite element model to a finite number of data points (such as a finite number of forces and directions). In some embodiments, a response surface method can be used to generate a surrogate model to generate a polynomial model that approximates the behavior of the finite element model. Other surrogate model types can include kriging, a more generalized Bayesian method, gradient enhanced kriging (GEK), radial basis functions, support vector machines, spatial mapping, artificial neural networks, and Bayesian networks.

[0229] A more detailed simulation for determining forces and appliance shape to achieve a target occlusion may include a finite element model of both the patient's anatomy (including teeth, gums, jaws, and other anatomical structures) and clinical data, and the appliance may be used to simulate the movement of the jaw. Using the finite element model and the target occlusion, the simulation may determine modifications to the thickness map of the appliance to achieve the target occlusion.

[0230] At block 1906, a desired thickness map of the occlusal surface of the appliance is determined based on the surrogate model. The thickness map may include the thickness at each location or shell element location on the occlusal service of the appliance in order to achieve the target occlusion.

[0231] Although the foregoing disclosure uses specific block diagrams, flow charts, and examples to illustrate various embodiments, a wide variety of hardware, software, or firmware (or any combination thereof) configurations may be used to implement each block diagram component, flow chart step, operation, and / or component described and / or illustrated herein, individually and / or collectively. In addition, any disclosure of components contained within other components should be considered exemplary in nature, as many other architectures may be implemented to achieve the same functionality.

[0232] In some examples, all or part of the example systems disclosed herein may represent portions of a cloud computing or network-based environment. A cloud computing environment may provide various services and applications via the Internet. These cloud-based services (e.g., software as a service, platform as a service, infrastructure as a service, etc.) may be accessed through a web browser or other remote interface. The various functions described herein may be provided through a remote desktop environment or any other cloud-based computing environment.

[0233] In various embodiments, all or part of the example systems disclosed herein can facilitate multi-tenancy within a cloud-based computing environment. In other words, the software modules described herein can configure a computing system (e.g., a server) to facilitate multi-tenancy for one or more of the functions described herein. For example, one or more modules in the software modules described herein can program a server so that two or more clients (e.g., customers) can share an application running on the server. A server programmed in this manner can share applications, operating systems, processing systems, and / or storage systems among multiple customers (i.e., tenants). One or more modules described herein can also divide the data and / or configuration information of a multi-tenant application for each customer so that one customer cannot access the data and / or configuration information of another customer.

[0234] According to various embodiments, all or part of the example systems disclosed herein can be implemented in a virtual environment. For example, the modules and / or data described herein can reside and / or execute in a virtual machine. As used herein, the term "virtual machine" generally refers to any operating system environment abstracted from computing hardware by a virtual machine manager (e.g., a hypervisor). Additionally or alternatively, the modules and / or data described herein can reside and / or execute in a virtualization layer. As used herein, the term "virtualization layer" generally refers to any data layer and / or application layer covering an operating system environment and / or abstracted from an operating system environment. The virtualization layer can be managed by a software virtualization solution (e.g., a file system filter), which presents the virtualization layer as if it is part of the underlying basic operating system. For example, a software virtualization solution can redirect calls that were originally directed to a location within a basic file system and / or a registry to a location in the virtualization layer.

[0235] In some examples, all or part of the example systems disclosed herein may represent multiple parts of a mobile computing environment. The mobile computing environment may be implemented by a variety of mobile computing devices, including mobile phones, tablet computers, e-book readers, personal digital assistants, wearable computing devices (e.g., computing devices with head-mounted displays, smart watches, etc.), etc. In some examples, the mobile computing environment may have one or more different features, including, for example, reliance on battery power, presenting only one foreground application at any given time, remote management features, touch screen features, location and motion data (e.g., provided by a global positioning system, a gyroscope, an accelerometer, etc.), a restricted platform that limits modifications to system-level configurations and / or limits the ability of third-party software to inspect the behavior of other applications, controls that limit the installation of applications (e.g., only from approved application stores), etc. The various functions described herein may be provided for the mobile computing environment and / or may interact with the mobile computing environment.

[0236] In addition, all or a portion of the example systems disclosed herein may represent multiple parts of one or more systems, interact with parts of one or more systems, consume data generated by one or more systems, and / or generate data consumed by one or more systems for information management. As used herein, the term "information management" may refer to the protection, organization, and / or storage of data. Examples of systems for information management may include, but are not limited to, storage systems, backup systems, archiving systems, replication systems, high availability systems, data search systems, virtualization systems, and the like.

[0237] In some embodiments, all or part of the example systems disclosed herein may represent multiple parts of one or more information security systems, generate data protected by one or more information security systems, and / or communicate with one or more information security systems. As used herein, the term "information security" may refer to control of access to protected data. Examples of systems for information security may include, but are not limited to, systems that provide managed security services, data loss prevention systems, identity authentication systems, access control systems, encryption systems, policy compliance systems, intrusion detection and protection systems, electronic discovery systems, etc.

[0238] The process parameters and step sequences described and / or shown herein are provided as examples only and may be changed as desired. For example, although the steps shown and / or described herein may be shown or discussed in a particular order, the steps do not necessarily need to be performed in the order shown or discussed. The various example methods described and / or shown herein may also omit one or more of the steps described or shown herein, or include additional steps in addition to those disclosed.

[0239] Although various embodiments have been described and / or shown herein in the context of a fully functional computing system, one or more of these example embodiments may be distributed in various forms as a program product, regardless of the specific type of computer-readable medium used to actually perform the distribution. The embodiments disclosed herein may also be implemented using software modules that perform certain tasks. These software modules may include scripts, batch processing, or other executable files that may be stored on a computer-readable storage medium or in a computing system. In some embodiments, these software modules may configure a computing system to perform one or more of the example embodiments disclosed herein.

[0240] As described herein, the computing devices and systems described and / or illustrated herein broadly represent any type or form of computing device or system capable of executing computer-readable instructions such as those contained within the modules described herein. In their most basic configuration, these computing devices may each include at least one memory device and at least one physical processor.

[0241] As used herein, the term "memory" or "memory device" generally refers to any type or form of volatile or non-volatile storage device or medium capable of storing data and / or computer-readable instructions. In one example, a memory device can store, load, and / or maintain one or more of the modules described herein. Examples of memory devices include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, hard disk drive (HDD), solid-state drive (SSD), optical drive, cache, one or more variations or combinations of the same, or any other suitable memory.

[0242] In addition, the term "processor" or "physical processor" as used herein generally refers to any type or form of hardware-implemented processing unit capable of interpreting and / or executing computer-readable instructions. In one example, the physical processor can access and / or modify one or more modules stored in the above-mentioned memory device. Examples of physical processors include, but are not limited to, microprocessors, microcontrollers, central processing units (CPUs), field programmable gate arrays (FPGAs) implementing soft-core processors, application specific integrated circuits (ASICs), variations or combinations of one or more of the same components, or any other suitable physical processors.

[0243] Although shown as separate elements, the method steps described and / or illustrated herein may represent multiple portions of a single application. In addition, in some embodiments, one or more of these steps may represent or correspond to one or more software applications or programs that, when executed by a computing device, may cause the computing device to perform one or more tasks, such as method steps.

[0244] In addition, one or more of the devices described herein may transform data, physical devices, and / or representations of physical devices from one form to another. Additionally or alternatively, one or more of the modules described herein may transform a processor, volatile memory, non-volatile memory, and / or any other portion of a physical computing device from one form of computing device to another form of computing device by executing on a computing device, storing data on a computing device, and / or otherwise interacting with a computing device.

[0245] Those skilled in the art will recognize that any process or method disclosed herein may be modified in many ways. The process parameters and order of steps described and / or illustrated herein are given as examples only and may be changed as desired. For example, although the steps shown and / or described herein may be shown or discussed in a particular order, the steps do not necessarily need to be performed in the order shown or discussed.

[0246] The various exemplary methods described and / or shown herein can also omit one or more steps described or shown herein, or include additional steps except those steps disclosed. In addition, the steps of any method disclosed herein can be combined with any one or more steps of any other method disclosed herein.

[0247] A processor as described herein may be configured to perform one or more steps of any method disclosed herein.Alternatively or in combination, a processor may be configured to combine one or more steps of one or more methods as disclosed herein.

[0248] Unless otherwise indicated, the terms "connected to" and "coupled to" (and their derivatives) used in the specification and claims should be interpreted as allowing both direct and indirect (i.e., via other elements or components) connections. In addition, the terms "a" or "an" as used in the specification and claims are interpreted to mean "at least one of them." Finally, for ease of use, the terms "including" and "having" (and their derivatives) used in the specification and claims are interchangeable with the word "comprising" and should have the same meaning as the word "comprising".

[0249] The processors disclosed herein may be configured with instructions to perform any one or more steps of any method disclosed herein.

[0250] It should be understood that although the terms "first", "second", "third", etc. may be used herein to describe various layers, elements, components, regions, or portions, they do not refer to any particular order or sequence of events. These terms are only used to distinguish one layer, element, component, region, or portion from another layer, element, component, region, or portion. Without departing from the teachings of the present disclosure, a first layer, element, component, region, or portion as described herein may be referred to as a second layer, element, component, region, or portion.

[0251] As used herein, the term "or" is used inclusively to refer to items in alternatives and combinations.

[0252] As used herein, characters such as numbers represent similar elements.

[0253] This disclosure includes the following numbered clauses.

[0254] Item 1: A method for additively manufacturing an orthodontic appliance, the method comprising: receiving a digital model of the appliance; processing the digital model of the appliance to modify the digital model based on predicted deviations during manufacturing to generate a first updated digital model of the appliance; determining whether the predicted deviations of a physical appliance additively manufactured based on the first updated digital model of the appliance are acceptable; and, outputting the first updated digital model of the appliance to manufacture the physical appliance by additive manufacturing.

[0255] Clause 2: The method of clause 1 further comprising: receiving real-time manufacturing parameters during manufacturing of the physical appliance; processing the first updated digital model to determine a predicted deviation of the physical appliance based on the real-time manufacturing parameters; and modifying the digital model based on the predicted deviation.

[0256] Clause 3: A method according to any of clauses 1-2, wherein determining that a predicted deviation of a physical appliance additively manufactured based on a first updated digital model of the appliance is acceptable comprises: determining that a predicted deviation of the physical appliance additively manufactured based on the first updated digital model of the appliance exceeds a threshold; and updating the first updated digital model of the appliance.

[0257] Clause 4: The method of any of clauses 1-3, wherein the predicted deviation during manufacturing is based on one or more parameters.

[0258] Clause 5: The method of any of clauses 1-4, wherein the one or more parameters include appliance geometry parameters.

[0259] Clause 6: The method of any of clauses 1-5, wherein the appliance geometry parameter comprises an angle of an appliance surface or a thickness of the appliance at a location on the appliance.

[0260] Clause 7: The method of any of clauses 1-6, wherein the one or more parameters include manufacturing parameters.

[0261] Clause 8: The method of any one of clauses 1-7, wherein the manufacturing parameters include material type, exposure time, exposure power, or material.

[0262] Clause 9: The method of any one of clauses 1-8, wherein the real-time parameter comprises material temperature, ambient temperature or ambient humidity.

[0263] Clause 10: A method according to any one of clauses 1-9, wherein the prediction model is used to generate the prediction deviation.

[0264] Clause 11: The method of any of clauses 1-10, wherein the prediction model is an empirical model.

[0265] Clause 12: A method according to any one of clauses 1-11, wherein the predictive model is a machine learning model.

[0266] Clause 13: A method as described in any of clauses 1-12, wherein the machine learning model is a neural network.

[0267] Clause 14: The method of any one of clauses 1-13, further comprising: training the neural network based on previously manufactured physical components.

[0268] Clause 15: The method of any of clauses 1-14, wherein the training is further based on manufacturing parameters and deviations between the geometry of the manufactured physical component and a digital model used to manufacture the manufactured physical component.

[0269] Clause 16: The method of any of clauses 1-15, wherein the training of the neural network further comprises registering a digital model used to manufacture the manufactured physical component with the digital model of the physical component.

[0270] Clause 17: The method according to any one of clauses 1-16 also includes: generating a digital image of a physical manufacturing slice of the first updated digital model; comparing the geometry of the physical manufacturing slice of the first updated digital model depicted in the digital image with the geometry of the corresponding slice of the first updated digital model; and updating the next slice of the first updated digital model based on the comparison.

[0271] Clause 18: The method according to any one of clauses 1-17 also includes: generating a digital model of a physical manufacturing slice of the first updated digital model; comparing the geometry of the physical manufacturing slice of the first updated digital model depicted in the digital model with the geometry of the corresponding slice of the first updated digital model; and, updating the geometry of the slice of the first updated digital model based on the comparison to generate an updated slice.

[0272] Clause 19: The method according to any one of clauses 1-18 further includes: making updated slices.

[0273] Clause 20: The method of any of clauses 1-19, wherein the digital model of the physical manufacturing slice is based on a 2D digital image of the manufacturing slice.

[0274] Item 21: A system for additively manufacturing an orthodontic appliance, the system comprising: a processor; and a memory comprising instructions that, when executed by the processor, enable the system to: receive a digital model of an appliance; process the digital model of the appliance to modify the model based on predicted deviations during manufacturing to generate a first updated digital model of the appliance; determine whether the predicted deviations of a physical appliance additively manufactured based on the first updated digital model of the appliance are acceptable; and, output the first updated digital model of the appliance to manufacture the physical appliance by additive manufacturing.

[0275] Clause 22: A system according to clause 21, wherein the instructions, when executed by the processor, further enable the system to: receive real-time manufacturing parameters during manufacturing of the physical appliance; process the first updated digital model to determine a predicted deviation of the physical appliance based on the real-time manufacturing parameters; and, modify the digital model based on the predicted deviation.

[0276] Clause 23: The system of any of clauses 21-22, wherein the instructions, when executed by the processor, further enable the system to: determine that a predicted deviation of the physical appliance exceeds a threshold; and update the first updated digital model of the appliance.

[0277] Clause 24: The system of any of clauses 21-23, wherein the predicted deviation during manufacturing is based on one or more parameters.

[0278] Clause 25: The system of any of clauses 21-24, wherein the one or more parameters include appliance geometry parameters.

[0279] Clause 26: The system of any of clauses 21-25, wherein the appliance geometry parameter comprises an angle of an appliance surface or a thickness of the appliance at a location of the appliance.

[0280] Clause 27: The system of any of clauses 21-26, wherein the one or more parameters include manufacturing parameters.

[0281] Clause 28: The system of any of clauses 21-27, wherein the manufacturing parameters include material type, exposure time, exposure power, or material.

[0282] Clause 29: A system according to any of clauses 21-28, wherein the real-time parameter comprises material temperature, ambient temperature or ambient humidity.

[0283] Clause 30: The system of any of clauses 21-29, wherein the prediction model is used to generate a prediction deviation.

[0284] Clause 31: The system of any of clauses 21-30, wherein the predictive model is an empirical model.

[0285] Clause 32: A system as described in any of clauses 21-31, wherein the predictive model is a machine learning model.

[0286] Clause 33: A system as described in any of clauses 21-32, wherein the machine learning model is a neural network.

[0287] Clause 34: The system of any of clauses 21-33, wherein the instructions, when executed by the processor, further enable the system to: train a neural network based on previously manufactured physical components.

[0288] Clause 35: The system of any of clauses 21-34, wherein the training is further based on manufacturing parameters and deviations between the geometry of the manufactured physical component and a digital model used to manufacture the manufactured physical component.

[0289] Clause 36: The system of any of clauses 21-35, wherein the instructions that, when executed by the processor, cause the system to train the neural network further cause the system to register a digital model used to manufacture the manufactured physical component with the digital model of the physical component.

[0290] Clause 37: A system according to any of clauses 21-36, wherein the instructions, when executed by the processor, further enable the system to: generate a digital image of a physical manufacturing slice of the first updated digital model; compare the geometry of the physical manufacturing slice of the first updated digital model depicted in the digital image with the geometry of a corresponding slice of the first updated digital model; and, based on the comparison, update the next slice of the first updated digital model.

[0291] Clause 38: A system according to any of clauses 21-37, wherein the instructions, when executed by the processor, further enable the system to: generate a digital model of a physical manufacturing slice of the first updated digital model; compare the geometry of the physical manufacturing slice of the first updated digital model depicted in the digital model with the geometry of the corresponding slice of the first updated digital model; and, based on the comparison, update the geometry of the slice of the first updated digital model to generate an updated slice.

[0292] Clause 39: The system of any of clauses 21-38, wherein the instructions, when executed by the processor, further enable the system to: manufacture the updated slice by additive manufacturing.

[0293] Clause 40: The system of any of clauses 21-39, wherein the digital model of the physical manufacturing slice is based on a 2D digital image of the manufacturing slice.

[0294] Clause 41: The system of any one of clauses 21-41, further comprising: an additive manufacturing machine.

[0295] Item 42: A method for additive manufacturing an appliance, the method comprising: receiving a digital model of an appliance having a plurality of tooth receiving cavities and an occlusal surface, the plurality of tooth receiving cavities being shaped to move one or more teeth of a patient; generating a first thickness map based on the digital model of the appliance; receiving a target orthodontic change to the patient's dentition; simulating an interaction of the appliance with the patient's dentition to achieve the target orthodontic change; and, generating a modified thickness map of the digital model of the appliance based on the simulation; and, outputting the digital model of the appliance with the modified thickness map to manufacture a physical appliance by additive manufacturing.

[0296] Clause 43: The method of clause 42, further comprising: manufacturing the physical appliance based on the digital model of the appliance having the modified thickness map by additive manufacturing.

[0297] Clause 44: The method of any of Clauses 42-43, wherein the first thickness map comprises thickness values ​​associated with each portion of the digital model of the appliance.

[0298] Clause 45: The method of any of clauses 42-44, wherein the first thickness map comprises a plurality of elements, wherein a position and a thickness are associated with each element to define a shape of the digital model of the appliance.

[0299] Clause 46: A method according to any of clauses 42-45, wherein the elements are intersections of shell elements or vertices.

[0300] Clause 47: The method of any of clauses 42-46, wherein the target orthodontic change is tooth movement.

[0301] Clause 48: The method of any of clauses 42-47, wherein the tooth movement intrudes upon the first tooth.

[0302] Clause 49: The method of any of clauses 42-48, wherein simulating interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating changes in an occlusal portion of the thickness map with respect to a tooth intrusion force on the first tooth.

[0303] Clause 50: The method of any of clauses 42-49, wherein generating a modified thickness map of the digital model of the appliance based on the simulation comprises increasing thickness values ​​of the thickness map of an occlusal portion of the digital model of the appliance at a tooth receiving cavity of a tooth.

[0304] Clause 51: The method of any of clauses 42-50, wherein the tooth movement is rotating the tooth.

[0305] Clause 52: The method of any of clauses 42-51, wherein simulating interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating a change in the occlusal interproximal thickness map with respect to a tooth rotational force on the first tooth.

[0306] Clause 53: A method according to any one of clauses 42-52, wherein the modified thickness map of the digital model of the braces generated based on the simulation includes increasing the thickness values ​​of the thickness map of the first occlusal interproximal portion and the second occlusal interproximal portion of the digital model of the braces between the tooth receiving cavity of the tooth and the first adjacent tooth and the second adjacent tooth.

[0307] Clause 54: A method according to any one of clauses 42-53, wherein the modified thickness map of the digital model of the braces generated based on the simulation includes reducing the thickness values ​​of the thickness map of the third occlusal interproximal portion and the fourth occlusal interproximal portion of the digital model of the braces between the tooth receiving cavity of the tooth and the first adjacent tooth and the second adjacent tooth.

[0308] Clause 55: The method of any of clauses 42-54, wherein the first portion is a lingual portion between the tooth and a first adjacent tooth, and the second portion is a buccal portion between the tooth and a second adjacent tooth.

[0309] Clause 56: The method of any of clauses 42-55, wherein the third portion is a buccal portion between the tooth and a first adjacent tooth, and the second portion is a lingual portion between the tooth and a second adjacent tooth.

[0310] Clause 57: The method of any of clauses 42-56, wherein the target orthodontic change is target occlusal stability.

[0311] Clause 58: The method of any of clauses 42-57, wherein simulating interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating changes in the occlusal portion of the thickness map with respect to the patient's occlusal stability.

[0312] Clause 59: The method of any of clauses 42-58, wherein generating a modified thickness map of the digital model of the appliance based on the simulation comprises modifying the thickness map to form a bite block on an occlusal surface of the digital model of the appliance.

[0313] Clause 60: The method of any of clauses 42-59, wherein generating a modified thickness map of the digital model of the appliance based on the simulation comprises modifying the thickness map to form a bite block receiving cavity on an occlusal surface of the digital model of the appliance.

[0314] Clause 61: The method of any of clauses 42-60, wherein generating a modified thickness map of the digital model of the appliance based on the simulation comprises reducing a thickness of a portion of the thickness map of an incisor surface of the tooth receiving cavity.

[0315] Clause 62: A method according to any one of clauses 42-61, wherein the brace is a first brace, and the method further comprises: generating a modified thickness map of the digital model of the second brace based on a simulation of the interaction of the second brace with the patient's bite, the modification comprising modifying the thickness of a portion of the thickness map of the incisor surface of the tooth receiving cavity to match the incisor surface of the tooth receiving cavity of the first brace.

[0316] Clause 63: The method of any of clauses 42-62, wherein the target orthodontic change is a target occlusal deocclusion.

[0317] Clause 64: The method of any of clauses 42-63, wherein simulating the interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating a change in an occlusal portion of the thickness map with respect to a deocclusion of the patient's bite.

[0318] Clause 65: The method of any of clauses 42-64, wherein generating a modified thickness map of the digital model of the appliance based on the simulation comprises increasing the thickness of an occlusal portion of the thickness map on an occlusal surface of the digital model of the appliance to provide a target occlusal deocclusion.

[0319] Clause 66: The method of any of clauses 42-65, wherein the target orthodontic change is a reduced appliance activation energy.

[0320] Clause 67: The method of any of clauses 42-66, wherein simulating the interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating a change in the bite thickness map with respect to an activation energy of the appliance.

[0321] Clause 68: A method according to any of clauses 42-67, wherein generating a modified thickness map of a digital model of the appliance based on the simulation includes thinning the thickness of an occlusal portion of the thickness map on an occlusal surface of the digital model of the appliance to provide a reduced appliance activation energy.

[0322] Clause 69: A system for additive manufacturing of an orthodontic appliance, the system comprising: a processor; and a memory comprising instructions that, when executed by the processor, cause the system to perform the method of any one of clauses 42-68.

[0323] Clause 70: A system for additive manufacturing of the orthodontic appliance of clause 69, further comprising: an additive manufacturing machine.

[0324] Item 71: A method for additive manufacturing of an appliance, the method comprising: receiving a digital model of an appliance having a plurality of tooth-receiving cavities shaped to move one or more teeth and a biting surface of a patient; receiving a target orthodontic change to the patient's dentition; simulating an interaction of the appliance with the patient's dentition to achieve the target orthodontic change; and, generating a modified thickness of the digital model of the appliance based on the simulation; and, outputting the digital model of the appliance having the modified thickness for use in manufacturing a physical appliance by additive manufacturing.

[0325] Clause 72: The method of clause 71, further comprising: manufacturing the physical appliance by additive manufacturing based on the digital model of the appliance having the modified thickness.

[0326] Clause 73: The method of any of clauses 71-72, wherein the target orthodontic change is tooth movement.

[0327] Clause 74: The method of any of clauses 71-73, wherein the tooth movement intrudes upon the first tooth.

[0328] Clause 75: The method of any of clauses 71-74, wherein simulating the interaction of the appliance with the patient's dentition to achieve the target orthodontic change comprises simulating a change in the thickness occlusal portion with respect to a tooth intrusion force on the first tooth.

[0329] Clause 76: The method of any of clauses 71-75, wherein generating a modified thickness of the digital model of the appliance based on the simulation comprises increasing a thickness value of a thickness of an occlusal portion of the digital model of the appliance at a tooth receiving cavity of the tooth.

[0330] Clause 77: The method of any of clauses 71-76, wherein the tooth movement is rotating the tooth.

[0331] Clause 78: The method of any of clauses 71-77, wherein simulating interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating a change in occlusal interproximal thickness with respect to a tooth rotational force on the first tooth.

[0332] Clause 79: A method according to any one of clauses 71-78, wherein the modified thickness of the digital model of the braces generated based on the simulation includes increasing the thickness value of the first occlusal interproximal portion and the second occlusal interproximal portion of the digital model of the dental braces between the tooth receiving cavity and the first adjacent tooth and the second adjacent tooth.

[0333] Clause 80: A method according to any one of clauses 71-79, wherein the modified thickness of the digital model of the braces generated based on the simulation includes reducing the thickness values ​​of the third occlusal interproximal portion and the fourth occlusal interproximal portion of the digital model of the dental braces between the tooth receiving cavity and the first adjacent tooth and the second adjacent tooth.

[0334] Clause 81: The method of any of clauses 71-80, wherein the first portion is a lingual portion between the tooth and a first adjacent tooth, and the second portion is a buccal portion between the tooth and a second adjacent tooth.

[0335] Clause 82: The method of any of clauses 71-81, wherein the third portion is a buccal portion between the tooth and a first adjacent tooth, and the second portion is a lingual portion between the tooth and a second adjacent tooth.

[0336] Clause 83: The method of any of clauses 71-82, wherein the target orthodontic change is a target occlusal stability.

[0337] Clause 84: The method of any of clauses 71-83, wherein simulating the interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating a change in the thickness occlusal portion with respect to the patient's occlusal stability.

[0338] Clause 85: The method of any of clauses 71-84, wherein generating a modified thickness of the digital model of the appliance based on the simulation comprises modifying the thickness to form a bite block on an occlusal surface of the digital model of the appliance.

[0339] Clause 86: The method of any of clauses 71-85, wherein generating a modified thickness of the digital model of the appliance based on the simulation comprises modifying the thickness to form a bite block receiving cavity on an occlusal surface of the digital model of the appliance.

[0340] Clause 87: The method of any of clauses 71-86, wherein generating the modified thickness of the digital model of the appliance based on the simulation comprises reducing the thickness of a portion of the thickness of the incisor surface of the tooth receiving cavity.

[0341] Clause 88: A method according to any one of clauses 71-87, wherein the brace is a first brace, and the method further comprises: generating a modified thickness of a digital model of the second brace based on a simulation of the interaction of the second brace with the patient's bite, the modification comprising modifying the thickness of a portion of the thickness of the incisor surface of the tooth receiving cavity to match the incisor surface of the tooth receiving cavity of the first brace.

[0342] Clause 89: The method of any of clauses 71-88, wherein the target orthodontic change is a target occlusal deocclusion.

[0343] Clause 90: The method of any of clauses 71-89, wherein simulating the interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating a change in the thickness of the occlusal portion with respect to the patient's bite deocclusion.

[0344] Clause 91: The method of any of clauses 71-90, wherein generating the modified thickness of the digital model of the appliance based on the simulation comprises increasing the thickness of the occlusal portion of the thickness on the occlusal surface of the digital model of the appliance to provide a target occlusal deocclusion.

[0345] Clause 92: The method of any of clauses 71-91, wherein the target orthodontic change is a reduced appliance activation energy.

[0346] Clause 93: The method of any of clauses 71-92, wherein simulating the interaction of the appliance with the patient's dentition to achieve a target orthodontic change comprises simulating a change in bite thickness with respect to an activation energy of the appliance.

[0347] Clause 94: A method according to any of clauses 71-93, wherein the modified thickness of the digital model of the appliance generated based on the simulation includes thinning the thickness of an occlusal portion of the thickness on the occlusal surface of the digital model of the appliance to provide a reduced activation energy of the appliance.

[0348] Clause 95: A system for additive manufacturing of an orthodontic appliance, the system comprising: a processor; and a memory comprising instructions that, when executed by the processor, cause the system to perform the method of any of clauses 71-94.

[0349] Clause 96: A system for additive manufacturing of an orthodontic appliance according to clause 95, further comprising: an additive manufacturing machine.

[0350] The embodiments of the present disclosure have been shown and described as described herein, and are provided by way of example only. One of ordinary skill in the art will recognize many adaptations, changes, variations, and substitutions that do not depart from the scope of the present disclosure. Several alternatives and combinations of the embodiments disclosed herein may be utilized without departing from the scope of the present disclosure and the invention disclosed herein. Therefore, the scope of the present invention shall be limited only by the scope of the appended claims and their equivalents.

Claims

1. A method for additive manufacturing of an orthodontic appliance, the method comprising: Receive a digital model of the appliance; processing the digital model of the appliance to modify the digital model based on predicted deviations during manufacturing to generate a first updated digital model of the appliance; determining whether a predicted deviation of a physical appliance additively manufactured based on the first updated digital model of the appliance is acceptable; and The first updated digital model of the appliance is output to manufacture the physical appliance by additive manufacturing of the physical appliance.

2. The method according to claim 1, further comprising: receiving real-time manufacturing parameters during manufacturing of the physical appliance; processing the first updated digital model to determine a predicted deviation of the physical appliance based on the real-time manufacturing parameters; and The digital model is modified based on the prediction deviation.

3. The method according to any one of claims 1 to 2, further comprising: Determining that the prediction deviation of the physical appliance exceeds a threshold; as well as The first updated digital model of the appliance is updated.

4. The method according to any one of claims 1 to 3, wherein: The predicted deviation during manufacturing is based on one or more parameters.

5. The method according to any one of claims 1 to 4, wherein: The one or more parameters include appliance geometry parameters.

6. The method according to any one of claims 1 to 5, wherein: The appliance geometry parameters include the angle of the appliance surface or the thickness of the appliance at the location of the appliance.

7. The method according to any one of claims 1 to 6, wherein: The one or more parameters include manufacturing parameters.

8. The method according to any one of claims 1 to 7, wherein: The manufacturing parameters include material type, exposure time, exposure power or material.

9. The method according to any one of claims 1 to 8, wherein: Real-time parameters include material temperature, ambient temperature or ambient humidity.

10. The method according to any one of claims 1 to 9, wherein: A prediction model is used to generate the prediction deviation.

11. The method according to any one of claims 1 to 10, wherein: The prediction model is an empirical model.

12. The method according to any one of claims 1 to 11, wherein: The predictive model is a machine learning model.

13. The method according to any one of claims 1 to 12, wherein: The machine learning model is a neural network.

14. The method according to any one of claims 1 to 13, further comprising: The neural network is trained based on previously manufactured physical components.

15. The method according to any one of claims 1 to 14, wherein: The training is also based on manufacturing parameters and deviations between the geometry of the manufactured physical component and a digital model used to manufacture the manufactured physical component.

16. The method according to any one of claims 1 to 15, wherein: The training of the neural network also includes registering the digital model used to manufacture the manufactured physical component with the digital model of the physical component.

17. The method according to any one of claims 1 to 16, further comprising: generating a digital image of a physical manufacturing slice of the first updated digital model; comparing the geometry of the physically manufactured slice of the first updated digital model depicted in the digital image with the geometry of a corresponding slice of the first updated digital model; as well as A next slice of the first updated digital model is updated based on the comparison.

18. The method according to any one of claims 1 to 17, further comprising: generating a digital model of a physical manufacturing slice of the first updated digital model; comparing the geometry of the physical manufacturing slice of the first updated digital model depicted in the digital model with the geometry of a corresponding slice of the first updated digital model; as well as The geometry of the slice of the first updated digital model is updated based on the comparison to generate an updated slice.

19. The method according to any one of claims 1 to 18, further comprising: The updated slice is manufactured.

20. The method according to any one of claims 1 to 19, wherein: The digital model of the physical manufacturing slice is based on a 2D digital image of the manufacturing slice.

21. A system for manufacturing an orthodontic appliance, the system comprising: processor; as well as A memory comprising instructions which, when executed by the processor, cause the system to perform a method according to any one of claims 1 to 20.

22. The system of claim 21, further comprising: Manufacturing machines.

23. A method for additively manufacturing an appliance, the method comprising: receiving a digital model of an appliance having a plurality of tooth-receiving cavities and an occlusal surface, the plurality of tooth-receiving cavities being shaped to move one or more teeth of a patient; receiving targeted orthodontic changes to the patient’s dentition; simulating interaction of the appliance with the patient's dentition to achieve the target orthodontic change; as well as generating a modified thickness of the digital model of the appliance based on the simulation; as well as The digital model of the appliance having the modified thickness is output for fabrication of a physical appliance by additive manufacturing.

24. The method according to claim 23, further comprising: The physical appliance is manufactured by additive manufacturing based on the digital model of the appliance having the modified thickness.

25. The method according to any one of claims 23 to 24, wherein: The target orthodontic change is tooth movement.

26. The method according to any one of claims 23 to 25, wherein: The tooth movement is intrusion into the first tooth.

27. The method according to any one of claims 23 to 26, wherein: Simulating interaction of the appliance with the patient's dentition to achieve the target orthodontic change includes simulating changes in the occlusal portion of the thickness with respect to tooth intrusion forces on the first tooth.

28. The method according to any one of claims 23 to 27, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes increasing a thickness value of the thickness of an occlusal portion of the digital model of the appliance at a tooth receiving cavity of the tooth.

29. The method according to any one of claims 23 to 28, wherein: The tooth movement is rotation of the teeth.

30. The method according to any one of claims 23 to 29, wherein: Simulating interaction of the appliance with the patient's dentition to achieve the target orthodontic change includes simulating changes in occlusal interproximal thickness with respect to tooth rotational forces on the first tooth.

31. The method according to any one of claims 23 to 30, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes increasing a thickness value of the thickness of a first occlusal interproximal portion and a second occlusal interproximal portion of the digital model of the appliance between a tooth receiving cavity of the tooth and a first adjacent tooth and a second adjacent tooth.

32. The method according to any one of claims 23 to 31, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes reducing thickness values ​​of the thickness of a third occlusal interproximal portion and a fourth occlusal interproximal portion of the digital model of the appliance between a tooth receiving cavity of the tooth and a first adjacent tooth and a second adjacent tooth.

33. The method according to any one of claims 23 to 32, wherein: The first portion is a lingual portion between the tooth and the first adjacent tooth, and the second portion is a buccal portion between the tooth and the second adjacent tooth.

34. The method according to any one of claims 23 to 33, wherein: The third portion is a buccal portion between the tooth and a first adjacent tooth, and the second portion is a lingual portion between the tooth and a second adjacent tooth.

35. The method according to any one of claims 23 to 34, wherein: The target orthodontic change is target occlusal stability.

36. The method according to any one of claims 23 to 35, wherein: Simulating interaction of the appliance with the patient's dentition to achieve the target orthodontic change includes simulating changes in the occlusal portion of the thickness with respect to occlusal stability of the patient.

37. The method according to any one of claims 23 to 36, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes modifying the thickness to form a bite block on the occlusal surface of the digital model of the appliance.

38. A method according to any one of claims 23 to 37, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes modifying the thickness to form a bite block receiving cavity on the occlusal surface of the digital model of the appliance.

39. The method according to any one of claims 23 to 38, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes reducing the thickness of a portion of a thickness of an incisor surface of a tooth receiving cavity.

40. The method according to any one of claims 23 to 39, wherein: The brace is a first brace, and the method further comprises generating a modified thickness of a digital model of the second brace based on a simulation of the interaction of the second brace with a patient's bite, the modification comprising modifying the thickness of a portion of a thickness of an incisor surface of a tooth receiving cavity to cooperate with the incisor surface of the tooth receiving cavity of the first brace.

41. A method according to any one of claims 23 to 40, wherein: The target orthodontic change is the target occlusal-deocclusal.

42. The method according to any one of claims 23 to 41, wherein: Simulating interaction of the appliance with the patient's dentition to achieve the target orthodontic change includes simulating changes in the occlusal portion of the thickness with respect to a occlusal deocclusion of the patient.

43. The method according to any one of claims 23 to 42, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes increasing a thickness of an occlusal portion of the thickness on the occlusal surface of the digital model of the appliance to provide the target occlusal deocclusion.

44. The method according to any one of claims 23 to 43, wherein: The target orthodontic change is reduced appliance activation energy.

45. The method according to any one of claims 23 to 44, wherein: Simulating the interaction of the appliance with the patient's dentition to achieve the target orthodontic change includes simulating changes in bite thickness with respect to activation energy of the appliance.

46. ​​A method according to any one of claims 23 to 45, wherein: Generating a modified thickness of the digital model of the appliance based on the simulation includes thinning an occlusal portion of the thickness on the occlusal surface of the digital model of the appliance to provide a reduced appliance activation energy.

47. A method according to any one of claims 23 to 46, wherein: The thickness is a thickness map.

48. A method according to any one of claims 23 to 47, wherein: The thickness map includes thickness values ​​associated with each portion of the digital model of the appliance.

49. The method according to any one of claims 23 to 48, wherein: The thickness map includes a plurality of elements, wherein a position and the thickness are associated with each element to define a shape of the digital model of the appliance.

50. The method according to any one of claims 23 to 49, wherein: The elements are intersections of shell elements or vertices.

51. A method according to any one of claims 23 to 50, wherein: The variation in thickness comprises a variation in the thickness profile.

52. A system for additive manufacturing of an orthodontic appliance, the system comprising: processor; as well as A memory comprising instructions which, when executed by the processor, cause the system to perform a method according to any one of claims 23 to 51.

53. The system for additively manufacturing an orthodontic appliance of claim 52, further comprising: Additive manufacturing machines.

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