A machining apparatus is provided with a machine learning device that performs machine learning. The machine learning device performs the machine learning by receiving the input of machining accuracy between a machining shape of a workpiece measured on-machine and design data on the workpiece and machining time of the workpiece measured by a measurement device. Based on a result of the machine learning, the machining apparatus changes machining conditions such that the machining accuracy increases and the machining time becomes as short as possible.

A machining time prediction device for a machine tool that controls at least one axis to machine a workpiece on the basis of a machining program, the machining time prediction device comprising: an analysis unit that analyzes the machining program and generates operation instructions for the axis; an execution control unit that supervises the execution of operation instructions, instructs the operation of the axis on the basis of the result of analyzing the machining program and determines that the operation of the axis is complete; an axis control unit that generates control commands on the basis of the axis operation instructions; a machining time prediction unit that measures the time required to execute the machining program and predicts the machining time; and an axis operation simulation unit that simulates the operation of the axis on the basis of the control commands and outputs virtual responses.

A machining time prediction device for a machine tool that controls at least one axis to machine a workpiece on the basis of a machining program, the machining time prediction device comprising: an analysis unit that analyzes the machining program and generates operation instructions for the axis; an execution control unit that supervises the execution of operation instructions, instructs the operation of the axis on the basis of the result of analyzing the machining program and determines that the operation of the axis is complete; an axis control unit that generates control commands on the basis of the axis operation instructions; a machining time prediction unit that measures the time required to execute the machining program and predicts the machining time; and an axis operation simulation unit that simulates the operation of the axis on the basis of the control commands and outputs virtual responses.

A cutting monitoring system used for a machine is provided. The cutting monitoring system includes a data capturing module, a database and a cutting control module. The data capturing module is configured to capture a motor current data of the machine and a tool wear data. The motor current data is used as a training data for a tool wear state prediction model to perform deep learning and forecasting. The database is configured to establish a tool wear database for the comparison of a tool wear state. The tool wear state prediction model outputs a tool wear state prediction data to the cutting control module. The cutting control module judges whether the tool wear state is normal according to the tool wear state prediction data.