Dental machining system for predicting machining time for manufacturing dental restorations / appliances

Abstract

The present invention relates to a dental machining system for manufacturing a dental restoration / orthotic device, comprising: a dental machine tool (1), comprising: a dental blank holder, which is used to hold at least one dental blank (2) in a movable manner relative to one or more dental tools (3); one or more drive units (4), each of which is used to hold one or more dental tools (3) in a movable manner; a control unit, which is used to control the dental blank holder and the drive unit (4) based on the construction data of the dental restoration / orthotic device and a plurality of machining processes dedicated to manufacturing the dental restoration / orthotic device from the dental blank (2); characterized in that the control unit is also suitable for executing a trained artificial intelligence algorithm, which is suitable for predicting the machining time for manufacturing the dental restoration / orthotic device based on input data, the input data comprising: process parameters, which respectively define the machining processes; and a mapping map, which comprises information on the target geometric shapes of the dental restoration / orthotic device constructed based on the machining processes.

Description

Technical Field

[0001] The present invention relates to a dental machining system having a dental machine tool for manufacturing a dental restoration / appliance from a dental blank by using one or more dental cutters. The present invention more particularly relates to a method for predicting machining time for manufacturing a dental restoration or a dental appliance using a dental machining system. Background Art

[0002] In general, a dental machining system has a dental machine for machining dental blanks, which are typically made of ceramic. The dental machine generally has one or more drive units, each of which holds at least one dental tool for machining the dental blank in a movable manner. The dental tools are respectively mounted to tool motors in the drive units. The dental tools can be replaced after their service life ends. The dental blank is mounted to a dental blank holder, which can move relatively relative to the dental tool. A control unit controls the operation of the dental machine. In general, CAD / CAM software runs on a PC connected to a control unit in a dental machining system. CAD / CAM software is used to digitally construct a dental restoration / appliance and provide a list of machining processes. The machining process is used to generate a time trajectory of the dental tool in the dental machine. Typically, before generating the time trajectory, the machining time required to complete the machining process is estimated. Different estimation methods are known. According to a known estimation method, a rough estimate is first made by using empirical values ​​based on parameters, such as the type of dental restoration / appliance, the number of caps in the dental restoration / appliance, the material of the dental blank, the degree of detail in the dental restoration / appliance, and the machining mode of the dental machine. Subsequently, a fine estimate is made based on specifically identifying the machining process used to manufacture the dental restoration / appliance. In the literature, machine learning methods are alternatively used to estimate machining time. Reference may be made to the article entitled "Estimation of Machining Time for CNC Manufacturing Using Neural Computing" by authors Saric, T., Simunovic, G., Simunovic, K., and Svalina, I., published in International Journal of Simulation Modelling. 15 (2016) 4, 663-675. In this method, process parameters of the machining process are used as input data.

[0003] In general, the differences in the geometry of dental restorations / appliances complicate the estimation of machining times. A typical factor complicating the estimation is the need to selectively remove excess material from specific areas of the restoration / appliance to be machined that are highly uneven (particularly undercuts). As a result, machining times can generally only be estimated with poor accuracy. Summary of the invention

[0004] An object of the present invention is to overcome the problems of the prior art and to provide a dental machining system for accurately predicting machining time for manufacturing dental restorations / appliances.

[0005] This object is achieved by the dental machining system according to the invention. Further subjects of the claims relate to further developments.

[0006] The present invention provides a dental machining system for manufacturing a dental restoration / orthodontic device. The dental machining system includes a dental machine tool, which includes: a dental blank holder, which is used to hold at least one dental blank in a movable manner relative to one or more dental tools; one or more drive units, each of which is used to hold one or more dental tools in a movable manner; and a control unit, which is used to control the dental blank holder and the drive unit based on the construction data of the dental restoration / orthodontic device and a plurality of machining processes dedicated to manufacturing the dental restoration / orthodontic device from the dental blank. The control unit is also suitable for executing a trained artificial intelligence algorithm, which is suitable for predicting the machining time for manufacturing the dental restoration / orthodontic device based on input data, the input data including: process parameters, the process parameters respectively defining the machining process; and mapping, the mapping including information about the target geometry of the dental restoration / orthodontic device constructed based on the machining process respectively.

[0007] The main advantageous effect of the present invention is that the dental machining system can accurately predict the machining time by means of a trained artificial intelligence algorithm with due consideration of the target geometry of the dental restoration / appliance. This makes it possible to accurately predict the machining time when selectively removing residual material from specific areas of the restoration / appliance to be machined, in particular undercuts. Another main advantageous effect of the present invention is that the artificial intelligence algorithm can be trained to adapt the prediction of the machining time to changes in the dental tool trajectory calculation scheme. Another main advantageous effect of the present invention is that the prediction based on the trained artificial intelligence algorithm can also take into account unknown factors that affect the machining time.

[0008] According to the present invention, different types of mappings can be used as input data. In an embodiment of the present invention, a first type of mapping is used to describe the target geometry of a dental prosthesis / appliance relative to the machining direction in the corresponding machining process. The machining processes to be performed by the dental machine tool are preferably provided in a sequential list. Each machining process in the list also includes information about the process parameters to be used to control the drive unit. For example, each machining process in the list includes a machining direction relative to the target geometry of the dental prosthesis / appliance and the type of dental tool to be used. The machining direction is parallel to the dental tool. These first types of mappings preferably describe the distance from the surface of the dental prosthesis / appliance to the reference plane of the drive unit. Alternatively, the first type of mapping may preferably describe the distance from the surface of the dental blank to the surface of the dental prosthesis / appliance. The first type of mapping preferably defines a two-dimensional distance map. Each distance map displays the distance by a numerical value. Alternatively, color or grayscale can be used. The input data may also include information about the type of dental tool used for the corresponding machining process for each first type of mapping. Due to the first type of map, the amount of remaining material can be determined based on the distance map and preferably taken into account together with the type of dental tool by a trained artificial intelligence algorithm to predict the machining time.

[0009] In an alternative embodiment of the present invention, a second type of mapping is used as input data. The second type of mapping is obtained via simulation, and describes the actual geometry of the remaining dental blank relative to the target geometry of the dental restoration / appliance after the corresponding machining process is simulated. In addition, in this embodiment, the machining process to be performed by the dental machine tool is preferably provided in a sequential list. The actual geometry of the remaining dental blank after the corresponding machining process is completed is obtained via simulation. The second type of mapping preferably describes the distance from the surface of the actual geometry of the remaining dental blank to the target geometry of the dental restoration / appliance after the corresponding machining process is simulated. The second type of mapping preferably defines a three-dimensional distance map. In addition, in this embodiment, each distance map shows the simulated distance by a numerical value. Alternatively, color or grayscale can be used. The surface of the actual geometry is preferably described by triangulation with attributes (attribute) respectively including the simulated distance. The attribute can be located at the highest point or triangle.

[0010] According to the invention, the control unit of the dental machining system generates input data based on the construction data of the dental restoration / appliance.Alternatively, the dental machining system may receive the input data and the construction data via an input device.

[0011] According to an embodiment of the present invention, the dental machining system has a training mode and an inference mode. In the inference mode, the control unit executes a trained artificial intelligence algorithm for predicting the machining time. In the training mode, the control unit is suitable for training the artificial intelligence algorithm for predicting the machining time for manufacturing the dental restoration / appliance based on input data, the input data comprising: process parameters, the process parameters respectively defining the machining process; and a mapping map, the mapping map comprising information about the target geometry of the dental restoration / appliance constructed based on the machining process respectively; and the actual machining time required to complete the machining process respectively. According to the present invention, the trained artificial intelligence algorithm is based on a neural network, preferably a convolutional neural network.

[0012] In training mode, the dental machining system uses previously generated or received input data derived from experiments or actual manufacturing operations. The actual machining time is obtained by monitoring the machining process. The database can be continuously updated with such input data for training mode.

[0013] According to an embodiment of the present invention, the dental machining system may also have a CAD / CAM module, which preferably includes a computer station such as a PC running CAD / CAM software. The trained artificial intelligence algorithm is preferably provided as part of the CAD / CAM module. The CAD / CAM module is preferably outside the dental machine tool and can be accessed through a network or the like. A plurality of different dental machine tools can use the trained artificial intelligence algorithm for reasoning. The CAD / CAM module can also be provided as part of the dental machine tool. The present invention also provides a CAD / CAM software for implementing the above-mentioned functions of the dental machining system. The CAD / CAM software has a computer-readable code for causing the computerized dental machining system to perform the functions. The CAD / CAM software is stored in a computer-readable storage medium. The storage medium may be portable or integrated. The storage medium may be located outside or inside the dental machining system. The storage medium may be accessible through a network or the like. The present invention can be applied to dental machine tools having various types of kinematics for moving dental blanks and dental cutters. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In the following description, further aspects and advantageous effects of the present invention will be described in more detail by using exemplary embodiments and with reference to the accompanying drawings, in which

[0015] Figure 1 - is a schematic partial perspective view of a dental machine tool of a dental machining system according to an embodiment of the present invention;

[0016] Figure 2- is a two-dimensional grayscale distance map of a dental restoration / appliance observed along a machining direction parallel to a dental tool according to an embodiment of the present invention;

[0017] Figure 3 - is a two-dimensional grayscale distance map of a dental restoration / appliance observed along a machining direction parallel to a dental tool according to another embodiment of the present invention;

[0018] Figure 4 - is a grayscale distance map of the actual geometry of the remaining dental blank before the simulation of the completion of the undercutting machining process relative to the target geometry of the dental restoration / appliance;

[0019] Figure 5 - is a grayscale distance map of the actual geometry of the remaining dental blank after the simulation of the undercut machining process is completed relative to the target geometry of the dental restoration / appliance.

[0020] The reference numerals shown in the drawings denote the elements listed below and will be referenced in the subsequent description of the exemplary embodiments:

[0021] 1. Dental machine tools

[0022] 2. Dental blanks

[0023] 2' remaining dental blank

[0024] 2a. Axis

[0025] 3. Dental tools

[0026] 4. Drive unit

[0027] 4a. Arm

[0028] 4b. Axis

[0029] 5a.,5b. Grayscale distance map

[0030] X,Y,Z: direction. DETAILED DESCRIPTION

[0031] Figure 1A dental machining system for manufacturing a dental restoration / orthodontic device is shown, comprising a dental machine tool (1), the dental machine tool (1) comprising: a dental blank holder for holding a dental blank (2) in a movable manner relative to a dental tool (3); two drive units (4), each of which is used to hold a dental tool (3) in a movable manner; and a control unit for controlling the dental blank holder and the drive units (4) based on the construction data of the dental restoration / orthodontic device and a plurality of machining processes dedicated to manufacturing the dental restoration / orthodontic device from the dental blank (2). Each drive unit (4) has a shaft (4b) and an arm (4a) radially fixed to the shaft (4b). Each shaft (4b) can be moved on the z-axis by a drive mechanism of the corresponding drive unit (4). Each arm (4a) can be moved around the z-axis by a drive mechanism. The dental tools (3) are respectively mounted to tool motors in the arms (4A). The dental blank (2) is connected to an axis (2a) by another drive mechanism, and the axis (2a) can move along the y-axis and rotate around the y-axis. The control unit has a training mode and an inference mode. In the inference mode, the control unit is also suitable for executing a trained artificial intelligence algorithm, which is suitable for predicting the machining time for manufacturing a dental restoration / orthotic based on input data, the input data comprising: process parameters, the process parameters respectively defining the machining process; and a mapping diagram, the mapping diagram comprising information about the target geometry of the dental restoration / orthotic constructed based on the machining process respectively. The process parameters include, for example, path distance, maximum feed rate, maximum acceleration, etc. The training mode will be described later. The control unit is suitable for generating input data based on the construction data of the dental restoration / orthotic. Alternatively, the input data and the construction data are input into the dental machining system via an input device.

[0032] In a first embodiment, the maps comprise maps of a first type, which respectively describe the target geometry of the dental restoration / appliance relative to a machining direction (z) in the machining process. The input data also include information about the type of dental tool (3) used for the corresponding machining process. The machining direction (z) is parallel to the dental tool (3). The maps of the first type also describe the distance from the surface of the dental restoration / appliance to a reference plane of the drive unit (4) or from the surface of the dental blank (2) to the surface of the dental restoration / appliance. The maps of the first type respectively define distance maps. Figure 2 and Figure 3 Each shows a two-dimensional grayscale distance map of a dental restoration / appliance viewed from a machining direction parallel to the dental tool according to another embodiment of the present invention. Alternatively, each distance map can display the distance by color or number. Figure 2In the figure, the light grey shows the deep fissures which lead to long machining times due to the extensive use of small dental cutters to selectively remove the remaining material. Figure 3 In the process, the target geometry is simple and leads to a short machining time. Therefore, the details of the target geometry have a large impact on the final machining time.

[0033] In a second embodiment, the map alternatively comprises a map of a second type, which has been obtained via simulation and describes the actual geometry of the remaining dental blank (2') relative to the target geometry of the dental restoration / appliance after the simulation of the corresponding machining process. The map of the second type describes the distance from the surface of the actual geometry of the remaining dental blank (2') to the target geometry of the dental restoration / appliance or vice versa after the simulation of the corresponding machining process. In particular, the simulation can calculate the distance from the target geometry to the actual geometry. These distances are obtained by simulation of the corresponding machining process. The surface of the actual geometry is described by triangulation with attributes that respectively include the simulated distances. The second type of map respectively defines the distance map obtained by simulation. Figure 4 A greyscale distance diagram of the actual geometry of the remaining dental blank (2') relative to the target geometry of the dental restoration / appliance before simulating the completion of the undercut machining process is shown. Figure 5 A greyscale distance diagram of the actual geometry of the remaining dental blank (2') after the simulated completion of the undercut machining process relative to the target geometry of the dental restoration / appliance is shown. Figure 4 and Figure 5 The grayscale distance map in is obtained by simulation. Alternatively, Figure 4 and Figure 5 The distance graph in can display the simulated distance in color or in numbers. Figure 5 In the figure, the light grey shows the specific areas of the restoration / appliance obtained by machining the simulated undercuts.

[0034] In the training mode, the control unit is suitable for training an artificial intelligence algorithm for predicting the machining time for manufacturing a dental restoration / appliance based on input data, the input data comprising: process parameters, which respectively define the machining process; and a mapping map, which comprises information about a target geometry of a dental restoration / appliance constructed based on the machining process, respectively; and an actual machining time required to complete the machining process, respectively.

[0035] The artificial intelligence algorithm is based on neural networks, in particular convolutional neural networks. With respect to the distance map of the dental restoration / appliance combined with the indication of the dental tool used, the convolutional neural network is able to learn geometrical properties with the help of training examples, which may require selective reworking (residual material removal) by means of fine dental tools. In addition, it may be possible to identify areas where only slow feeding is possible or areas where special material immersion processes (ZigZag) are required. These geometry-dependent properties also have a large impact on the final machining time. During the training of the artificial intelligence algorithm based on neural networks, the parameters of the neural network are learned by back propagation.

Claims

1. A dental machining system for manufacturing dental restorations / appliances, include: A dental machine tool (1), comprising: A dental blank holder for holding at least one dental blank (2) in a movable manner relative to one or more dental cutters (3); one or more drive units (4), each of which is used to hold one or more dental knives (3) in a movable manner, a control unit for controlling the dental blank holder and the drive unit (4) based on construction data of the dental restoration / appliance and a plurality of machining processes dedicated to manufacturing the dental restoration / appliance from the dental blank (2); in, The control unit is further adapted to perform: A trained artificial intelligence algorithm adapted to predict the machining time for manufacturing said dental restoration / appliance based on input data comprising: process parameters, the process parameters respectively defining the machining process; and A map comprising information about a target geometry of the dental restoration / appliance constructed based on the machining process, wherein the map comprises: a first type of map, wherein the first type of map describes the target geometry of the dental restoration / appliance relative to a machining direction (z) in the machining process, wherein the machining direction (z) is parallel to the dental tool (3), wherein the first type of map also describes a distance from a surface of the target geometry of the dental restoration / appliance to a reference plane of the drive unit (4) or a distance from a surface of the dental blank (2) to a surface of the target geometry of the dental restoration / appliance.

2. The dental machining system according to claim 1, It is characterized in that The maps of the first type respectively define distance maps.

3. The dental machining system according to claim 2, It is characterized in that Each distance map displays distances by color, grayscale, or number.

4. The dental machining system according to any one of claims 1 to 3, It is characterized in that The input data also include, for each map of the first type, information about the type of dental tool (3) to be used in the corresponding machining process.

5. The dental machining system according to claim 1, It is characterized in that The control unit is adapted to generate the input data based on construction data of the dental restoration / appliance.

6. The dental machining system according to claim 1, It is characterized in that The dental machining system further comprises an input device for receiving input data and configuration data.

7. The dental machining system according to claim 1, It is characterized in that The control unit is adapted to train an artificial intelligence algorithm for predicting a machining time for manufacturing the dental restoration / appliance based on input data comprising: process parameters, the process parameters respectively defining the machining process; and a map comprising information about a target geometry of a dental restoration / appliance, respectively, constructed based on the machining process; and the actual machining time required to complete the machining process, respectively.

8. A dental machining system for manufacturing dental restorations / appliances, include: A dental machine tool (1), comprising: A dental blank holder for holding at least one dental blank (2) in a movable manner relative to one or more dental cutters (3); one or more drive units (4), each of which is used to hold one or more dental knives (3) in a movable manner, a control unit for controlling the dental blank holder and the drive unit (4) based on construction data of the dental restoration / appliance and a plurality of machining processes dedicated to manufacturing the dental restoration / appliance from the dental blank (2); in, Wherein, the control unit is further adapted to perform: A trained artificial intelligence algorithm adapted to predict the machining time for manufacturing said dental restoration / appliance based on input data comprising: process parameters, the process parameters respectively defining the machining process; and A map comprising information about a target geometry of the dental restoration / orthodontic appliance, wherein the map comprises: a map of a second type which has been obtained by simulation and which describes the actual geometry of a remaining dental blank (2') relative to the target geometry of the dental restoration / orthodontic appliance after the simulation of a corresponding machining process, wherein the map of the second type describes the distance from the surface of the actual geometry of the remaining dental blank (2') to the surface of the target geometry of the dental restoration / orthodontic appliance or vice versa after the simulation of a corresponding machining process.

9. The dental machining system according to claim 8, It is characterized in that The surface of the actual geometry or the target geometry is described by triangulation, which in each case has properties including distances.

10. The dental machining system according to claim 8 or 9, It is characterized in that The maps of the second type respectively define a distance map.

11. The dental machining system according to claim 10, It is characterized in that Each distance map displays distances by color, grayscale, or number.

12. The dental machining system according to claim 9, It is characterized in that The control unit is adapted to generate the input data based on construction data of the dental restoration / appliance.

13. The dental machining system according to claim 9, It is characterized in that The dental machining system further comprises an input device for receiving input data and configuration data.

14. The dental machining system according to claim 9, It is characterized in that The control unit is adapted to train an artificial intelligence algorithm for predicting a machining time for manufacturing the dental restoration / appliance based on input data comprising: process parameters, the process parameters respectively defining the machining process; and a map comprising information about a target geometry of a dental restoration / appliance, respectively, constructed based on the machining process; and the actual machining time required to complete the machining process, respectively.

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