Dental machining system for generating machining process parameters

Abstract

The present invention relates to a dental processing system for manufacturing a dental restoration, comprising: a dental tool machine (1), comprising: a dental blank holder for holding one or more dental blanks (2) that can be relatively moved relative to one or more dental tools (3); one or more drive units (4), each of which is used to movably hold at least one dental tool (3) for processing the dental blank (2); a determination unit for determining the type of each dental blank (2); an adjustment device for allowing a user to adjust a processing time, a quality level of the dental restoration, and a safety level of the dental restoration and the dental tool (3) against processing damage; characterized in that it further comprises: a control unit, which is further adapted to: execute a trained artificial intelligence algorithm, the trained artificial intelligence algorithm being adapted to generate process parameters for processing based on the type of the dental blank (2), the processing time, the quality level of the dental restoration, and the safety level of the dental restoration and the dental tool (3) against processing damage; calculate a time trajectory of the dental tool (3) used for processing based on construction data of the dental restoration and the generated process parameters; and control the dental blank holder and the drive unit (4) based on the calculated time trajectory.

Description

Technical Field

[0001] The invention relates to a dental machining system having a dental machine tool for producing a dental restoration or a dental appliance from a dental blank by using one or more dental tools. The invention more particularly relates to a method for generating process parameters for machining a dental blank. Background Art

[0002] Typically, a dental processing system has a dental machine tool for processing dental blanks. The dental machine tool typically has one or more drive units, each of which movably holds at least one dental tool for processing dental blanks. 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 that can move relatively relative to the dental tool. A control unit controls the operation of the dental processing system. Typically, CAD / CAM software is executed, for example, on a PC connected to the dental machine tool. CAD / CAM software is typically used to digitally provide construction data for a dental restoration to be manufactured. The CAD / CAM software further generates a time trajectory of the dental tool in the dental machine tool based on the construction data and the process parameters of the processing. Thereafter, the dental blank holder and the drive unit are controlled based on the time trajectory of the dental tool. Typically, a user inputs the type of dental blank via a user interface of the dental machine tool. The user is often allowed to discretely adjust the machining time (e.g. very fast, fast, normal), the quality level of the dental restoration (e.g. very high, high, normal), and / or the safety level of the dental restoration and the dental tool against machining damage (e.g. very high, high, normal) via a graphical user interface of the CAD / CAM software. In complex test series, process parameters for the dental machine tool (such as the feed rate of the dental blank, the path distance of the dental tool, the feed rate of the dental tool into the material, the rotation speed of the dental tool, etc.) have to be defined manually for each type of dental blank and, for example, each quality level of the dental restoration and each safety level desired by the user.

[0003] So far, empirical values ​​from previous tests have been used as a basis for defining process parameters. Based on empirical values, process parameters are defined for basic settings. With the help of suitable methods (e.g., statistical design of experiments (DoE)), a process parameter space can be configured, which is then checked with the help of real refinement on a dental machine tool. A rough process parameter model can be derived from these results of the inspection. Based on this model, a process parameter combination can then be determined, which guarantees a favorable behavior with respect to the above-mentioned optimization variables (such as processing time, quality level of dental restorations (e.g., no debris), safety level of dental restorations (e.g., no damage to dental restorations or dental tools), dental tool service life, etc.). The process parameter combination must be further checked and / or improved by further testing of dental machine tools. The problem with this prior art method is that a complex series of many tests must be carried out for different / new types of dental blanks, different / new types of dental machine tools, different / new operating modes of dental machine tools, or different / new types of framework conditions. However, this is very time-consuming and labor-intensive. When process parameters depend continuously on optimization variables (eg dental tool wear conditions, dynamics or loads), the experimental effort is too great. Summary of the invention

[0004] The object of the present invention is to overcome the problems of the prior art and to provide a dental machining system which can accurately generate process parameters for machining to manufacture dental restorations / appliances.

[0005] This object has been achieved by a dental machining system as defined in claim 1. The subject matter of the dependent claims relates to further embodiments and developments.

[0006] According to an embodiment of the present invention, the dental processing system utilizes artificial intelligence, such as neural networks, etc. According to the present invention, the dental processing system has a training mode and an inference mode. The inference mode will be briefly disclosed first. In the dental processing system of the present invention, in the inference mode, the control unit is further adapted to: execute a trained artificial intelligence algorithm, which is adapted to generate process parameters for processing based on the type of dental blank, processing time, quality level of dental restorations, and safety level of dental restorations and dental tools against processing damage; calculate the time trajectory of the dental tool for processing based on the construction data of the dental restoration and the generated process parameters; and control the dental blank holder and the drive unit based on the calculated time trajectory. The process parameters include at least one of the rotation speed of the dental tool, the feed rate of the dental tool into the material, the path distance of the dental tool, the limit values ​​of the processing force and torque acting on the dental tool, the feed rate of the dental blank, etc.

[0007] A major advantageous effect of the invention is that the trained artificial intelligence algorithm saves the knowledge resulting from past machining (or test series) concerning the process parameters used in the dental machine tool in order to simplify or even replace future machining (or test series). As a result, the test engineer is therefore automatically supported in the process parameter setting by the results of all previous tests. Another major advantageous effect of the invention is that due to the large amount of knowledge learned from past machining (or test series), the trained artificial intelligence algorithm can, for example, generate significantly different process parameters in a continuous range. Another major advantageous effect of the invention is that the trained artificial intelligence algorithm continuously improves the generation of process parameters based on, for example, optimization of machining speed versus quality level while ensuring a level of safety.

[0008] According to an embodiment of the invention, the determination unit is further adapted to determine the type of dental tool and the wear condition of the dental tool. In this embodiment, the type of dental tool and the wear condition of the dental tool may be input into the dental tool machine by a user, or retrieved from a data storage located directly on the dental tool and / or at a remote location by using an RFID tag on the dental tool or the like. In this embodiment, in the inference mode, the control unit is further adapted to execute a trained artificial intelligence algorithm, which is adapted to generate process parameters for machining further based on the type of dental tool and the wear condition of the dental tool. Thereby, the process parameters may be generated taking into account such specific properties of the dental tool.

[0009] According to an embodiment of the present invention, the dental processing system further comprises a sensing unit for sensing dynamic quantities related to the dental tool. In this embodiment, in the inference mode, the control unit is further adapted to: execute a trained artificial intelligence algorithm, which is adapted to generate process parameters for processing further based on the sensed dynamic quantities; and adaptively control the dental blank holder and the drive unit based on the generated process parameters during processing. The dynamic quantity may correspond to at least the position, velocity, acceleration, vibration, force acting on the corresponding dental tool, torque, supply current to a dental tool motor of the corresponding dental tool, or sound generated by the corresponding dental tool of the corresponding dental tool. Thereby, the generated process parameters may be suitable for real-time processing taking into account the dynamic characteristics of the dental tool.

[0010] According to an embodiment of the invention, in the inference mode, the control unit is further adapted to: determine the dental tool load along the time trajectory; execute the trained artificial intelligence algorithm, which is adapted to generate process parameters for machining further based on the time trajectory and the determined dental tool load; and adaptively control the dental blank holder and the drive unit based on the generated process parameters during machining. Thereby, the process parameters may be generated taking into account the dental tool load. For example, the dental tool load may be estimated based on an analysis of the progression of the spatial tool trajectory.

[0011] According to an embodiment of the invention, the adjustment means further allows the user to adjust the processing time, the quality level of the dental restoration, and the safety level of the dental restoration and the dental tool against processing damage in a discrete manner or alternatively in a continuous manner. Preferably, 3 different parameter groups for 3 different processing modes can be adjusted discretely. Continuous adjustment can be performed using software sliders. Thus, the process parameters can be generated even more differently.

[0012] Subsequently, the training mode will be briefly disclosed. In the training mode, the dental processing system uses data derived from experiments or real manufacturing operations. The storage medium can be continuously updated with such data for the training mode and used as a database. According to an embodiment of the present invention, the dental processing system may also have a CAD / CAM module, which preferably includes a computer station such as a PC that executes the 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 tool machine and can be accessed through a network or the like. A plurality of different dental tool machines can use the trained artificial intelligence algorithm in the reasoning mode. The CAD / CAM module can also be provided as part of the dental tool machine. The present invention also provides CAD / CAM software for implementing the above-mentioned functions of the dental processing system. The CAD / CAM software has a computer-readable code for enabling the computerized dental processing system to perform 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 processing system. The storage medium may be accessible through a network or the like. The present invention can be applied to dental tool machines with various types of kinematic and dynamic capabilities for moving dental blanks and dental tools.

[0013] According to an embodiment of the invention, in the training mode, the control unit is further adapted to train an artificial intelligence algorithm for generating process parameters for machining based on the type of dental blank, the standardized machining time, the quality level of the dental restoration and the safety level of the dental restoration and the dental tools and the process parameters for previously completed machining. The standardized machining time is preferably determined based on the measured machining time and the construction data of the dental restoration. For example, the standardized machining time may be obtained by dividing the measured machining time by the number of crowns and / or the surface area of ​​the dental restoration, etc. Typically, the construction data implicitly or explicitly include such information specific to the dental restoration and may be derived for the purpose of standardization.

[0014] According to an embodiment of the invention, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for machining further based on the type of dental tool and the wear condition of the dental tool before starting a previously completed machining and / or after completing a previously completed machining. The dental tool wear condition usually changes with its operating time. Therefore, the cutting condition at the beginning of the tool life is different from the cutting condition at the end of the tool life. The trained artificial intelligence algorithm enables continuous process parameter tracking during the entire tool life. In this way, the quality of the resulting manufactured dental restoration can be maintained, whether using a new dental tool or a used dental tool, and the dental tool can therefore be optimally utilized.

[0015] According to an embodiment of the present invention, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for the machining further based on sensed dynamic quantities involving the dental tool for previously completed machining. Thereby, the trained artificial intelligence algorithm improves process parameter generation based on the dynamic quantities.

[0016] According to an embodiment of the invention, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for machining further based on the time trajectory of the dental tool relative to the dental blank and the dental tool load determined along the time trajectory for previously completed machining. Thereby, the trained artificial intelligence algorithm improves process parameter generation based on aspects of the dental tool load (e.g. material-dependent speed reduction).

[0017] According to an embodiment of the invention, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for the processing of a new type of dental blank further based on the type of the new dental blank, the standardized processing time, the quality level of the dental restoration and the safety level of the dental restoration and the dental tool against processing damage and the process parameters of at least one completed processing of the new dental blank. Thereby, the trained artificial intelligence algorithm enables to collect new knowledge about the properties of the new material in only a few trials when setting the processing for the new material. Moreover, the remaining knowledge is generated by the past knowledge of the trained artificial intelligence algorithm about other materials. Especially in large laboratories, there is often a desire to optimize the processing process for unverified materials. With the present invention, the customer is provided with means to effectively generate process parameters for unknown materials.

[0018] According to an embodiment of the present invention, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for processing using the new type of dental tool machine based on the type of the new dental tool machine, the standardized processing time, the quality level of the dental restoration and the safety level of the dental restoration and the dental tool against processing damage, and the process parameters for at least one completed processing using the new dental tool machine. Thus, the trained artificial intelligence algorithm achieves learning to process using the new machine type based on several real experiments.

[0019] According to an embodiment of the present invention, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for processing using the new trajectory calculation algorithm based on changes in the trajectory calculation algorithm, standardized processing time, quality level of the dental restoration and safety level of the dental restoration and dental tools against processing damage, and process parameters for at least one completed processing using the new trajectory calculation algorithm. Thus, the trained artificial intelligence algorithm enables learning processing under changes in framework conditions (e.g., trajectory calculation algorithms based on several real experiments). This increases the flexibility of the manufacturing process.

[0020] According to an embodiment of the present invention, the quality level of the dental restoration comprises at least one of surface smoothness, chipping level and precision of the dental restoration. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In the following description, further aspects and advantageous effects of the present invention will be described in more detail by using exemplary embodiments and by referring to the accompanying drawings, in which:

[0022] Figure 1 FIG. 4 is a partial schematic diagram of a dental machine tool in a dental processing system according to an embodiment of the present invention.

[0023] The reference numbers shown in the drawings represent the elements listed below and will be referred to in the subsequent description of the exemplary embodiments:

[0024] 1. Dental machine tools

[0025] 2. Dental blanks

[0026] 2a. Axis

[0027] 3. Dental tools

[0028] 4. Drive unit

[0029] 4a. Arm

[0030] 4b. Axis

[0031] X, Y, Z: direction. DETAILED DESCRIPTION

[0032] Figure 1A dental processing system for manufacturing a dental restoration is shown, comprising: a dental tool machine (1), comprising: a dental blank holder for holding a dental blank (2) that can be relatively moved relative to a dental tool (3); two drive units (4), each of which is used to movably hold a dental tool (3) for processing the dental blank (2); a determination unit for determining the type of each dental blank (2); and an adjustment device for allowing a user to adjust the desired processing time, the quality level of the dental restoration, and the safety level of the dental restoration and the dental tool (3) against processing damage. Each drive unit (4) has a shaft (4b) and an arm (4a) radially fixed to the shaft (4b). Each shaft (4b) can be moved along the z-axis to the dental blank (2) or away from the dental blank (2) by the drive mechanism of the corresponding drive unit (4). Each arm (4a) can be moved around the z-axis by the drive mechanism. The dental tools (3) are respectively mounted to the tool motors in the arms (4a). The dental blank (2) is connected to an axis (2a) which can be moved along the y-axis and rotated around the y-axis by another drive mechanism. The dental processing system comprises a control unit. The control unit has a training mode and an inference mode. First, the inference model will be described. In the inference mode, the control unit is further adapted to: execute a trained artificial intelligence algorithm, which is adapted to generate process parameters for processing based on the type of dental blank (2), processing time, quality level of dental restorations, and safety level of dental restorations and dental tools (3) against processing damage; calculate the time trajectory of the dental tool (3) used for processing based on the construction data of the dental restoration and the generated process parameters; and control the dental blank holder and the drive unit (4) based on the calculated time trajectory. The process parameters include, for example, the rotation speed of the dental tool (3), the feed rate of the dental tool (3) into the material, the path distance of the dental tool (3), the limit values ​​for the processing force and torque acting on the dental tool (3), the feed rate of the dental blank (2), etc. The dental processing system calculates the construction data or receives the construction data from an external source. The quality level of the dental restoration includes at least one of surface smoothness, degree of chipping, and precision of the dental restoration.

[0033] In an embodiment, the determination unit is further adapted to determine the type of dental tool (3) and the wear condition of the dental tool (3); and, in the inference mode, the control unit is further adapted to execute a trained artificial intelligence algorithm, which is adapted to generate process parameters for machining further based on the type of dental tool (3) and the wear condition of the dental tool (3). The determination unit may use sensors such as RF sensors, touch sensors, etc., user input devices and / or databases for such purpose.

[0034] In an embodiment, the dental processing system further comprises: a sensing unit for sensing a dynamic quantity related to the dental tool (3); and, in an inference mode, the control unit is further adapted to: execute a trained artificial intelligence algorithm adapted to generate process parameters for processing further based on the sensed dynamic quantity; and adaptively control the dental blank holder and the drive unit (4) based on the generated process parameters during processing. The dynamic quantity corresponds to at least one of a position, a velocity, an acceleration, a vibration, a force acting on the corresponding dental tool (3), a torque, a supply current to a dental tool motor of the corresponding dental tool (3), or a sound generated by the corresponding dental tool (3).

[0035] In an embodiment, in the inference mode, the control unit is further adapted to: determine the load of the dental tool (3) along a calculated or sensed time trajectory; execute a trained artificial intelligence algorithm adapted to generate process parameters for machining further based on the time trajectory and the determined load of the dental tool (3); and adaptively control the dental blank holder and the drive unit (4) based on the generated process parameters during machining.

[0036] In an embodiment, in the inference mode, the adjustment device further allows the user to adjust the processing time, the quality level of the dental restoration, and the safety level of the dental restoration and the dental tool (3) against processing damage in a continuous manner, for example based on a preset range. Alternatively, the user may be allowed to adjust the processing time, the quality level of the dental restoration, and the safety level of the dental restoration and the dental tool (3) against processing damage in a discrete manner, for example based on one or more preset values.

[0037] In the following description, a training mode will be described.The training aims at learning the optimization of the triangles of machining time, quality level and safety level for different dental blank types from the knowledge of multiple past machinings (or test series). The knowledge may include, for each past machining, at least one of the process parameters, including the feed rate of the dental blank (2), the path distance of the dental tool (3), the feed rate of the dental tool (3) into the material, the rotation speed of the dental tool (3), the trajectory calculation algorithm used, the parameters of the dental tool (3) load algorithm, the parameters of any special treatments (such as immersion, path smoothing), the type of dental tool (3), the wear condition of the dental tool (3) before starting and / or completing machining, the type of dental blank (2) (e.g. its material), the machining time, the entire time trajectory of the dental tool (3) (including acceleration, velocity in each direction for each point thereof), the material removed according to the dental tool (3) load determination algorithm, the current to the tool motor, the forces and torques acting on the dental tool (2) obtained by sensor technology, the resulting quality level of the dental restoration, any special events (such as damage to the dental tool (2) or the dental restoration), the type of dental tool machine (including kinematic and dynamic capabilities). In the training mode, the control unit is further adapted to train an artificial intelligence algorithm for generating process parameters for machining based on the type of dental blank, the standardized machining time, the quality level of the dental restoration and the safety level of the dental restoration and the dental tool (3) and process parameters for previously completed machining. The standardized machining time is determined based on the measured machining time and features that can be derived from construction data of the dental restoration, such as the number of crowns and / or the surface area of ​​the dental restoration.

[0038] In an embodiment, the training is directed to learning the type and wear condition of the dental tool (3). In this embodiment, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for processing further based on the type of dental tool (3) and the wear condition of the dental tool (3) before starting a previously completed processing and / or after completing a previously completed processing. The wear condition of the dental tool (3) is given as a percentage, where 100% indicates that the dental tool (3) is substantially new and 0% indicates that the dental tool (3) is completely worn.

[0039] In an embodiment, the training is directed to learning the dynamic characteristics of the dental tool (3), such as process forces and torques. In this embodiment, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for the machining further based on sensed dynamic quantities involving the dental tool (3) of previously completed machining.

[0040] In an embodiment, the training is directed to learning the dental tool (3) load. In this embodiment, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for machining further based on the time trajectory of the dental tool (3) relative to the dental blank (2) and the dental tool (3) load determined along the time trajectory of previously completed machining.

[0041] In an embodiment, the training is directed to learning a new dental blank (2). In this embodiment, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for the processing of a new type of dental blank (2) further based on the type of new dental blank (2), the standardized processing time, the quality level of the dental restoration and the safety level of the dental restoration and the dental tool (3) against processing damage and the process parameters of at least one completed processing of the new dental blank (2). For example, for a certain type of dental blank (2) of "material A", training is performed using a number of related past processings (or test series) to generate process parameters in the most favorable or optimized combination. For a new "material B" of a certain type of dental blank (2), only orientation tests in non-optimized combinations are required. The results are fed back into the trained artificial intelligence algorithm. This can directly allow the most favorable or ideal optimal combination to be found based on the learned correlation with material A and the data of the orientation test, which then only has to be verified in the final test. Time-consuming tests for optimization regarding material B are no longer necessary.

[0042] In an embodiment, the training is aimed at learning a new dental machine tool (1). The dental machine tool (1) can vary in terms of kinematic and dynamic capabilities. In this embodiment, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for processing using a new type of dental machine tool (1) further based on the type of the new dental machine tool (1), the standardized processing time, the quality level of the dental restoration and the safety level of the dental restoration and the dental tool (3) against processing damage, and the process parameters for at least one completed processing using the new dental machine tool (1).

[0043] In an embodiment, the training is directed to learning the new trajectory calculation algorithm. In an embodiment, in the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for machining using the new trajectory calculation algorithm further based on changes in the trajectory calculation algorithm, the standardized machining time, the quality level of the dental restoration and the safety level of the dental restoration and the dental tool (3) against machining damage and process parameters for at least one completed machining using the new trajectory calculation algorithm.

Claims

1. A dental processing system for manufacturing a dental restoration / appliance, comprising: A dental machine tool (1), comprising: A dental blank holder for holding one or more dental blanks (2) that are relatively movable relative to one or more dental tools (3); one or more drive units (4), each of which is used to movably hold at least one dental tool (3) for machining the dental blank (2); a determination unit, the determination unit being used to determine the type of each dental blank (2); adjustment means for allowing a user to adjust at least one of a machining time, a quality level of the dental restoration / appliance, and a safety level of the dental restoration / appliance and dental tool (3) against machining damage; It is characterized by further comprising: A control unit, the control unit further being adapted to: executing a trained artificial intelligence algorithm adapted to generate process parameters for said machining based on at least one of said machining time, said quality level of said dental restoration / appliance and said safety level of said dental restoration / appliance and dental tool (3) against machining damage, said type of said dental blank (2), calculating a time trajectory of the dental tool (3) for the machining based on the construction data of the dental restoration / appliance and the generated process parameters, and The dental blank holder and the drive unit (4) are controlled based on the calculated time trajectory.

2. The dental processing system according to claim 1, characterized in that: The determination unit is further adapted to determine the type of the dental tool (3) and the wear condition of the dental tool (3); and The control unit is further adapted to: The trained artificial intelligence algorithm is executed, and the trained artificial intelligence algorithm is adapted to generate process parameters for the machining further based on the type of the dental tool (3) and the wear condition of the dental tool (3).

3. The dental processing system according to claim 1 or 2, characterized in that: Further including: a sensing unit for sensing dynamic quantities related to the dental tool (3); and The control unit is further adapted to: executing the trained artificial intelligence algorithm, the trained artificial intelligence algorithm being adapted to generate process parameters for the machining further based on the sensed dynamic quantities, and The dental blank holder and the drive unit (4) are adaptively controlled during machining based on generated process parameters.

4. The dental processing system according to claim 1 or 2, characterized in that: The control unit is further adapted to: determining a load of the dental tool (3) along the time trajectory of the dental tool (3), executing the trained artificial intelligence algorithm, the trained artificial intelligence algorithm being adapted to generate process parameters for the machining further based on the time trajectory and the determined dental tool (3) load, and The dental blank holder and the drive unit (4) are adaptively controlled during machining based on generated process parameters.

5. The dental processing system according to claim 1 or 2, characterized in that: The adjustment device further allows the user to adjust at least one of the machining time, the quality level of the dental restoration / appliance and the safety level of the dental restoration / appliance and dental tool (3) against machining damage in a continuous or discrete manner.

6. The dental processing system according to claim 1 or 2, characterized in that: The control unit is further adapted to: The artificial intelligence algorithm is trained to generate process parameters for the machining based on a standardized machining time, the quality level of the dental restoration / appliance and at least one of the safety levels of the dental restoration / appliance and the dental tool (3), the type of the dental blank and process parameters for a previously completed machining.

7. The dental processing system according to claim 6, characterized in that: The control unit is further adapted to: The artificial intelligence algorithm is trained to generate process parameters for the process further based on the type of the dental tool (3) and the wear condition of the dental tool (3) before starting a previously completed process and / or after completing the previously completed process.

8. The dental processing system according to claim 6, characterized in that: The control unit is further adapted to: The artificial intelligence algorithm is trained for generating process parameters for the machining further based on sensed dynamic quantities of previously completed machining involving the dental tool (3).

9. The dental processing system according to claim 6, characterized in that: The control unit is further adapted to: The artificial intelligence algorithm is trained for generating process parameters for the machining further based on the time trajectory of the dental tool (3) relative to the dental blank (2) and the dental tool (3) load determined along the time trajectory of previously completed machining.

10. The dental processing system according to claim 6, characterized in that: The control unit is further adapted to: The artificial intelligence algorithm is trained for generating process parameters for the machining of the new type of dental blank (2) further based on at least one of the standardized machining time, the quality level of the dental restoration / appliance and the safety level of the dental restoration / appliance and the dental tool (3) against machining damage, the type of new dental blank (2) and the process parameters of at least one previously completed machining of the new type of dental blank (2).

11. The dental processing system according to claim 6, characterized in that: The control unit is further suitable for: training the artificial intelligence algorithm to generate process parameters for the processing using the new type of dental machine tool (1) based on the standardized processing time, the quality level of the dental restoration / appliance, at least one of the safety levels of the dental restoration / appliance and the dental tool (3) against processing damage, the type of new dental machine tool (1) and the process parameters of at least one completed processing using the new type of dental machine tool (1).

12. The dental processing system according to claim 6, characterized in that: The control unit is further adapted to: The artificial intelligence algorithm is trained for generating process parameters for the processing using the new trajectory calculation algorithm based further on the standardized processing time, the quality level of the dental restoration / appliance and at least one of the safety levels of the dental restoration / appliance and the dental tool (3) against processing damage, changes in the trajectory calculation algorithm and process parameters of at least one completed processing using the new trajectory calculation algorithm.

13. The dental processing system according to claim 6, characterized in that: The standardized processing time is determined based on the measured processing time and the construction data of the dental restoration / appliance.

14. The dental processing system according to claim 1 or 2, characterized in that: The process parameters include at least one of the rotation speed of the dental tool (3), the feed rate of the dental tool (3) into the material, the path distance of the dental tool (3), limit values ​​for processing forces and torques acting on the dental tool (3), and the feed rate of the dental blank (2).

15. The dental processing system according to claim 1 or 2, characterized in that: The quality level of the dental restoration / appliance comprises at least one of surface smoothness, degree of chipping and precision of the dental restoration / appliance.

16. The dental processing system according to claim 3, characterized in that: The dynamic quantity corresponds to at least one of the position, velocity, acceleration, vibration of the corresponding dental tool (3), the force acting on the corresponding dental tool (3), the torque, the supply current to the dental tool motor of the corresponding dental tool (3) or the sound generated by the corresponding dental tool (3).

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