DENTAL MACHINING SYSTEM FOR GENERATING PROCESS PARAMETERS OF THE MACHINING

Abstract

A dental machining system for manufacturing a dental restoration, including: a dental tool machine which includes: a dental blank holder for holding one or more dental blanks relatively movable with respect to one or more dental tools; one or more driving units each for movably holding at least one dental tool for machining the dental blanks; a determination unit for determining the type of each dental blank; an adjustment device for allowing the user to adjust the machining time, a level of quality of the dental restoration, and a level of security of the dental restoration and dental tool against machining damage. The system further includes a control unit which executes a trained artificial intelligence algorithm adapted to generate process parameters for the machining.

Claims

1. A dental machining system for manufacturing a dental restoration/appliance comprising: a dental tool machine which comprises: a dental blank holder configured to hold one or more dental blank relatively movable with respect to one or more dental tools; one or more driving units each configured to movably hold at least one dental tool for machining the dental blanks; a determination unit configured to determine a type of each dental blank; an adjustment device configured to allow a user to adjust at least one of a machining time, a level of quality of the dental restoration/appliance, and a level of security of the dental restoration/appliance and dental tool against machining damage; wherein a control unit is configured to execute a trained artificial intelligence algorithm configured to generate process parameters for the machining based on the type of the dental blank, at least one of the machining time, the level of quality of the dental restoration/appliance, and the level of security of the dental restoration/appliance and dental tool against machining damage, wherein the control unit is configured to calculate a temporal trajectory of the dental tool for the machining based on construction data of the dental restoration/appliance and the generated process parameters, and wherein the control unit is configured to control the dental blank holder and the driving units based on the calculated temporal trajectory.

2. The dental machining system according to claim 1, wherein the determination unit is further configured to compute the type of the dental tool and the wear condition of the dental tool; and the control unit is further configured to execute the trained artificial intelligence algorithm configured to generate process parameters for the machining further base on the type of the dental tool and the wear condition of the denial tool.

3. The dental machining system according to claim 1 further comprising: a sensing unit configured to sense dynamical quantities relating to the dental tool; wherein the control unit is further configured to execute the trained artificial intelligence algorithm adapted to generate process parameters for the machining further based on the sensed dynamical quantities, and to adaptively control the dental blank holder and the driving units based on the generated process parameters during the machining.

4. The dental machining system according to claim 1, wherein the control unit is further adapted to determine a dental tool load along the temporal trajectory of the dental tool, and to execute the trained artificial intelligence algorithm configured to generate process parameters for the machining further based on the temporal trajectory and the determined dental tool load, and to adaptively control the dental blank holder and the driving units based on the generated process parameters during the machining.

5. The dental machining system according to claim 1, wherein the adjustment means further allows the user to adjust at least one of the machining time, the level of quality of the dental restoration/appliance, and the level of security of the dental restoration/appliance and dental tool against machining damage in a continuous manner or discrete manner.

6. The dental machining system according to claim 1, wherein the control unit is further configured to train the artificial intelligence algorithm for generating process parameters for the machining based on the type of the dental blank, process parameters used for a previously completed machining, and at least one of a normalized machining time, the level of quality of the dental restoration/appliance, and the level of security of the dental restoration/appliance and the dental tool.

7. The dental machining system according to claim 6, characterized in that the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for the machining further based on the type of the dental tool and the wear conditions of the dental tool before start and/or after completion of a previously completed machining.

8. The dental machining system according to claim 6, wherein the control unit is further configured to train the artificial intelligence algorithm for generating process parameters for the machining further based on the sensed dynamical quantities relating to the dental tool of a previously completed machining.

9. The dental machining system according to claim 6, wherein the control unit is further configured to train the artificial intelligence algorithm for generating process parameters for the machining further based on the temporal trajectory of the dental tool relative to the dental blank and the determined dental tool load along the temporal trajectory of a previously completed machining.

10. The dental machining system according to claim 6, wherein the control unit is further configured to train the artificial intelligence algorithm for generating process parameters for the machining of a new type of dental blank further based on the type of the new dental blank process parameters used for at least one previously completed machining of the new type dental blank, and at least one of the normalized machining time, the level of quality of the dental restoration/appliance, and the level of security of the dental restoration/appliance and dental tool against machining damage.

11. The dental machining system according to claim 6, wherein the control unit is further configured to train the artificial intelligence algorithm for generating process parameters for the machining with a new type of dental tool machine further based on the type of the new dental tool machine, process parameters used for at least one completed machining with the new type dental tool machine, and at least one of the normalized machining time, the level of quality of the dental restoration/appliance, and the level of security of the dental restoration/appliance and dental tool against machining damage.

12. The dental machining system according to claim 6, wherein the control unit is further configured to train the artificial intelligence algorithm for generating process parameters for the machining with a new trajectory calculation algorithm further based on the change in the trajectory calculation algorithm, process parameters used for at least one completed machining with the new trajectory calculation algorithm, and at least one of the normalized machining time, the level of quality of the dental restoration/appliance, and the level of security of the dental restoration/appliance and dental tool against machining damage.

13. The dental machining system according to claim 6, wherein the normalized machining time is determined based on the measured machining time and the construction data of the dental restoration/appliance.

14. The dental machining system according to claim 1, wherein the process parameters comprise at least one of a rotational speed of the dental tool, feed rates of the dental tool into the material, path distance of the dental tool, limit values for machining forces and torques acting on the dental tool, and feed rate of the dental blank.

15. The dental machining system according to claim 1, wherein the level quality of the dental restoration/appliance comprises at least one of the surface smoothness, the degree of chipping, and the precision of the dental restoration/appliance.

16. The dental machining system according to claim 3, characterized in that the dynamical quantity corresponds to at least one of the position, the speed, the acceleration, the vibration of the respective dental tool, the force, the torque acting on the respective dental tool, the supply current to a dental tool motor of the respective dental tool or the sound generated by the respective dental tool.

Description

BRIEF DESCRIPTION OF THE DRAWING

[0021] In the subsequent description, further aspects and advantageous effects of the present invention will be described in more detail by using exemplary embodiments and by reference to the drawing, wherein

[0022] FIG. 1—is partial schematic view of dental tool machine in a dental machining system of an embodiment according to the present invention.

[0023] The reference numbers shown in the drawing denote the elements as listed below and will be referred to in the subsequent description of the exemplary embodiments: [0024] 1. Dental tool machine [0025] 2. Dental blank [0026] 2a. Shaft [0027] 3. Dental tool [0028] 4. Driving unit [0029] 4a. Arm [0030] 4b. Shaft

[0031] X,Y,Z: Directions

[0032] FIG. 1 shows a dental machining system for manufacturing a dental restoration, comprising: a dental tool machine (1) which comprises: a dental blank holder for holding a dental blank (2) relatively movable with respect to the dental tools (3); two driving units (4) each for movably holding a dental tool (3) for machining the dental blank (2); a determination unit for determining the type of each dental blank (2); and an adjustment means for allowing the user to adjust the desired machining time, level of quality of the dental restoration, and level of security of the dental restoration and the dental tool (3) against machining damage. Each driving unit (4) has a shaft (4b) and an arm (4a) radially fixed to the shaft (4b). Each shaft (4b) can be moved in the z axis to or away from the dental blank (2) through a driving mechanism of the respective driving unit (4). Each arm (4a) can be moved around the z axis through the driving mechanism. The dental tools (3) are mounted to tool motors in the arm (4a) respectively. The dental blank (2) is joined to a shaft (2a) which can be moved along the y axis and rotated around the y axis through another driving mechanism. The dental machining 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 adapted to generate process parameters for the machining based on the type of the dental blank (2), the machining time, the level of quality of the dental restoration, and the level of security of the dental restoration and the dental tool (3) against machining damage , to calculate the temporal trajectory of the dental tool (3) for the machining based on construction data of the dental restoration and the generated process parameters, and to control the dental blank holder and the driving units (4) based on the calculated temporal trajectory. The process parameters comprise, for example, a rotational speed of the dental tool (3), feed rates of the dental tool (3) into the material, path distance of the dental tool (3), limit values for machining forces and torques acting on the dental tool (3), feed rate of the dental blank (2) and the like. The dental machining system calculates the construction data or receives it from an external source. The level of quality of the dental restoration comprises at least of one the surface smoothness, the degree of chipping, and the precision of the dental restoration.

[0033] In an embodiment, 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, in the inference mode, the control unit is further adapted to execute the trained artificial intelligence algorithm 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). The determination unit may use sensors such as RF sensors, touch sensors or the like, user input means and/or databases for such purpose.

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

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

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

[0037] In the subsequent description, the training mode will be described. The training is directed to learn from the knowledge of the plurality of past machining (or test series) the optimization of a triangle of machining time, the level of quality and the level of security for different dental blank types. 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 rates of the dental tool (3) into the material, the rotational speed of the dental tool (3), the trajectory calculation algorithm used, the parameters of the dental tool (3) load algorithm, parameters of any special treatments such as immersion, path smoothing, the type of the dental tool (3), the wear conditions of the dental tool (3) before start and/completion of the machining, the type of the dental blank (2) e.g., the material thereof, the machining time, the entire temporal trajectory of the dental tool (3) including for each point thereof the speed, the acceleration in each direction, the removed material according to a dental tool (3) load determination algorithm, the currents to the tool motors, the force and the torque acting on the dental tool (2) obtained through a sensor technology, the resulting level of quality of the dental restoration, any special occurrences like damages to the dental tool (2) or the dental restoration, the type of the dental tool machine including the kinematical and dynamical capacities. In the training mode, the control unit is further adapted to train the artificial intelligence algorithm for generating process parameters for the machining based on the type of the dental blank, a normalized machining time, the level of quality of the dental restoration, and the level of security of the dental restoration and the dental tool (3), and the process parameters used for a previously completed machining. The normalized machining time is determined based on the measured machining time and features derivable from the construction data of the dental restoration such as the number of caps and/or the surface area of the dental restoration and the like.

[0038] In an embodiment, the training is directed to learning the type and the 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 the machining further based on the type of the dental tool (3) and the wear condition of the dental tool (3) before start and/or after completion of a previously completed machining. The wear condition of the dental tool (3) is given as a percentage, wherein 100% indicates that the dental tool (3) is substantially new, and 0% indicates a that the dental tool (3) is completely worn.

[0039] In an embodiment, the training is directed to learning the dynamics of the dental tool (3) e.g., process forces and torques. In this embodiment, in the training mode, the control unit is further adapted to the train artificial intelligence algorithm for generating process parameters for the machining further based on the sensed dynamical quantities relating to the dental tool (3) of a 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 the machining further based on the temporal trajectory of the dental tool (3) relative to the dental blank (2) and the determined dental tool (3) load along the temporal trajectory of a 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 machining of a new type of dental blank (2) further based on the type of the new dental blank (2), the normalized machining time, the level of quality of the dental restoration, and the level of security of the dental restoration and the dental tool (3) against machining damage, and process parameters used for at least one completed machining of the new dental blank (2). For instance, for “material A” of a certain type of a dental blank (2), the training is performed with the plurality of related past machining (or test series) to generate the process parameters in a most advantageous or optimized combination. For a new “material B” of a certain type of a dental blank (2), only an orientation test in a non-optimized combination is required. The results are fed back into the trained artificial intelligence algorithm. This can directly allow to find the most advantageous, or ideally optimal combination on the basis of the correlations learned with material A and the data of the orienting test, which then only has to be validated in a final test. The time-consuming tests for the optimization with respect to material B are no longer necessary.

[0042] In an embodiment, the training is directed to learn a new dental tool machine (1). The dental tool machines (1) may vary in kinematical and dynamical capability. 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 with a new type of dental tool machine (1) further based on the type of the new dental tool machine (1), the normalized machining time, the level of quality of the dental restoration, and the level of security of the dental restoration and the dental tool (3) against machining damage, and process parameters used for at least one completed machining with the new dental tool machine (1).

[0043] In an embodiment, the training is directed to learn a 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 the machining with a new trajectory calculation algorithm further based on the change in the trajectory calculation algorithm, the normalized machining time, the level of quality of the dental restoration, and the level of security of the dental restoration and the dental tool (3) against machining damage, and process parameters used for at least one completed machining with the new trajectory calculation algorithm.