Patent ID: 12193895

The reference numbers shown in the drawings denote the elements as listed below and will be referred to in the subsequent description of the exemplary embodiments:1. Dental tool machine2. Dental blank2a. Shaft3. Dental tool4. Driving unit4a. Arm4b. Shaft5. Configuration fieldX1, X2, X3, Y1, Y2, Y3: Parameters for machining

FIG.1partly shows a dental tool machine (1) of a dental machining system for manufacturing a dental restoration. The dental tool machine (1) comprises: a dental blank holder which holds a dental blank (2) relatively movable with respect to the dental tools (3); two driving units (4) each movably holding a dental tool (3) for machining the dental blank (2); and a control unit adapted to control the dental blank holder and the driving units (4) based at least on a temporal trajectory of the dental tool (3) relative to the dental blank (2) and a spatial amount of material removal from the dental blank (2) along the temporal trajectory. Each driving unit (4) has a shaft (4b). An arm (4a) is radially fixed to each shaft (4b). Each driving unit (4) has a driving mechanism which can rotate the shaft (4b) about the z axis and reciprocate the shaft (4b) along the z axis. The dental tools (3) are held by tool motors which are located in the arms (4a) respectively. The dental blank (2) is joined to a shaft (2a). The shaft (2a) is connected to another driving mechanism which can rotate the shaft (2a) about the y axis and reciprocate the shaft (2a) along the y axis.

The control unit has a training mode and an inference mode. In the subsequent description first the inference mode will be described. The training mode will be described later. In the inference mode the control unit is adapted to execute a primary trained artificial intelligence algorithm adapted to predict dynamical quantities based on the temporal trajectory and, the spatial amount of material removal. The dynamical quantities correspond to one or more physically measurable quantities which relate to the respective dental tool (3) along the temporal trajectory. In the inference mode the control unit is also adapted to execute a secondary trained artificial intelligence algorithm adapted to predict the wear condition of the dental tool (3) based on the predicted dynamical quantities.

In an embodiment, the dynamical quantity corresponds at least to the speed, the acceleration, the vibration of the respective dental tool (3), or the force, the torque acting on the respective dental tool (3) or the supply current to a dental tool motor of the respective dental tool (3) or the sound generated by the respective dental tool (3). Herein, the speed, acceleration and the force may be measured along any of the x, y, z directions corresponding to the degrees of freedom of the dental tool machine (1). The speed may also comprise the speed of revolution of the dental tool (3).

In an embodiment, the wear condition of the dental tool (3) is predicted as a percentage. 100% indicates that the dental tool (3) is substantially new and 0% indicates a that the dental tool (3) is completely worn.

In an embodiment, the dental machining system further comprises: a first auxiliary means for recognizing the type of the dental blank (2) and the type of the dental tool (3); and a second auxiliary means for recognizing the actual wear condition of the dental tool (3). In this embodiment, the control unit is further adapted to execute the primary trained artificial intelligence algorithm which is further adapted to predict the dynamical quantities based on the temporal trajectory and the spatial amount of material removal, the type of the dental blank (2), the type of the dental tool (3), and the actual wear condition of the dental tool (3) before starting the machining. In this embodiment, the control unit is further adapted to execute the secondary trained artificial intelligence algorithm which is further adapted to predict the wear condition of the dental tool (3) based on the predicted dynamical quantities, and the actual wear condition of the dental tool (3) before starting the machining. The first auxiliary means and the second auxiliary means are optional, since the dental tool machine can also be operated with a default type of dental blank (2), a default type of dental tool (3), wherein the dental tool machine (1) is equipped initially with a new dental tool (3).

In an embodiment, the control unit determines before starting of the machining whether the predicted wear condition of the dental tool (3) will drop to a predetermined level before completion of the machining.

In an embodiment, the control unit determines a position along the temporal trajectory for interrupting the machining and to terminate use of the dental tool (3) based on the predicted wear condition of the dental tool (3).

In an embodiment, the dental machining system further comprises a display for displaying a configuration field (5) for allowing the user to manually adjust one or more parameters (X1-X3,Y1-Y3) of the forthcoming machining. The user may opt for manual adjustment through the user interface.FIG.2shows a configuration field (5) which is displayed on a display of the user interface of the dental tool machine (1). The parameters (X1-X3,Y1-Y3) relate to the temporal trajectory and the spatial amount of material removal. The parameters (X1-X3,Y1-Y3) shown inFIG.2are discrete so that the adjustment can be conducted by selecting the parameters (X1-X3,Y1-Y3). They may be alternatively continuously adjusted, for instance, through a software slider. As shown inFIG.2, when the user selects a set of parameters (X1,Y1), then the configuration field (5) correspondingly shows the predicted wear condition of the dental tool (3), i.e., 27% that will be attained at the end of the machining conducted with such selected parameters (X1,Y1). The number of parameters, their ranges etc., may be defined according to the application. They may include quality levels, speed levels and the like. In this embodiment, the control unit executes the first and secondary trained artificial intelligence algorithms so as to predict before start of the machining the wear condition of the dental tool (3) to be attained at the end of the machining for the respective adjustment and displays, on the display, information indicating the predicted wear condition of the dental tool (3) for the adjustment before start of the machining. The configuration field (5) is illustrated in form of a 3×3 matrix. Alternatively, it may be a continuous color map, wherein the colors indicate the wear condition of the dental tool (3).

The user may alternatively opt for automatic adjustment through the user interface. In an embodiment, the control unit automatically adjusts the parameters (X1-X3,Y1-Y3) of the machining based on the predicted wear condition of the dental tool (3).

In the subsequent description the training mode will be described. The training mode is conducted on a dental machining system which comprises one or more sensors for the measuring the dynamical quantities which relate one or more dental tools (4) when driven along the temporal trajectory with the spatial amount of material removal from the dental blank (2). In the training mode the control unit trains the primary artificial intelligence algorithm for predicting the dynamical quantities based on the temporal trajectory, the spatial amount of material removal, and the measured dynamical quantities. In the training mode the control unit trains the secondary artificial intelligence algorithm for predicting the wear condition of the dental tool (3) based on the predicted dynamical quantities and the actual wear condition of the dental tool (3). The secondary artificial intelligence algorithm may be alternatively trained on a dental machining system which doesn't have the sensors for the measuring the dynamical quantities. The dental tool machine (1) used for training the primary artificial intelligence algorithm has the same kinematics with the dental tool machine (1) used for training the secondary artificial intelligence algorithm. The inference mode can be run on a dental machining system which does not comprise the sensors for the measuring the dynamical quantities.

In an embodiment, the control unit trains the primary trained artificial intelligence algorithm for further predicting the dynamical quantities based on the temporal trajectory, the spatial amount of material removal, the measured dynamical quantities, the type of the dental blank (2), the type of the dental tool (3), and the actual wear condition of the dental tool (3). In this embodiment, the dental machining system has a first auxiliary means and the second auxiliary means as described above.