A method for operating a numerically controlled production machine includes defining a permissible value range determined by the design and construction of the production machine in which, in a normal operation during production of a workpiece, values representing a mechanical or electrical load described by acceleration and/or jolting of at least one component of the numerically controlled production machine are variable, and activating, for producing the workpiece, with a control signal a conservation operation for reducing the mechanical or electrical loads, wherein in the conservation operation the values of acceleration and/or jolting of the at least one component are variable within a part value range that is limited in comparison to the permissible value range.

A process plan optimization method for manufacturing a workpiece by adding a material in a plurality of layers is provided. The method includes: building a predicting model, the predicting model configured to predict a temperature variation of at least a portion of the workpiece; predicting an expected temperature variation of the portion of the workpiece to be manufactured during a given time period based on the predicting model and the process plan; and adjusting the process plan in response to the expected temperature variation of the portion failing to meet a preset condition, to make the expected temperature variation of the portion meet the preset condition.

A learning model is constructed for adjusting control information so that a cycle time becomes shorter while also avoiding the occurrence of overheating. A learning model construction device includes: an input data acquisition means that acquires, as input data, control information including a combination of an operation pattern of a spindle and parameters related to machining in a machine tool, and temperature information of the spindle prior to performing the machining based on the control information; a label acquisition means for acquiring temperature information of the spindle after having performed the machining based on the control information as a label; and a learning model construction means for constructing a learning model for temperature information of the spindle after having performed machining based on the control information, by performing supervised learning with a group of the input data and the label as training data.

A process plan optimization method for manufacturing a workpiece by adding a material in a plurality of layers is provided. The method includes: building a predicting model, the predicting model configured to predict a temperature variation of at least a portion of the workpiece; predicting an expected temperature variation of the portion of the workpiece to be manufactured during a given time period based on the predicting model and the process plan; and adjusting the process plan in response to the expected temperature variation of the portion failing to meet a preset condition, to make the expected temperature variation of the portion meet the preset condition.

The present disclosure provides a monitoring device, a monitoring method and a device for cutting a display substrate. The monitoring device includes an infrared temperature detection module configured to detect a temperature at a contacting position where a cutter wheel is in contact with the display substrate when cutting the display substrate with the cutter wheel, so as to acquire a temperature parameter at the contacting position; and a processing module configured to generate, based on the temperature parameter, a corresponding control parameter for controlling the process of cutting the display substrate.

A learning model is constructed for adjusting control information so that a cycle time becomes shorter while also avoiding the occurrence of overheating. A learning model construction device includes: an input data acquisition means that acquires, as input data, control information including a combination of an operation pattern of a spindle and parameters related to machining in a machine tool, and temperature information of the spindle prior to performing the machining based on the control information; a label acquisition means for acquiring temperature information of the spindle after having performed the machining based on the control information as a label; and a learning model construction means for constructing a learning model for temperature information of the spindle after having performed machining based on the control information, by performing supervised learning with a group of the input data and the label as training data.

A method for operating a numerically controlled production machine includes defining a permissible value range determined by the design and construction of the production machine in which, in a normal operation during production of a workpiece, values representing a mechanical or electrical load described by acceleration and/or jolting of at least one component of the numerically controlled production machine are variable, and activating, for producing the workpiece, with a control signal a conservation operation for reducing the mechanical or electrical loads, wherein in the conservation operation the values of acceleration and/or jolting of the at least one component are variable within a part value range that is limited in comparison to the permissible value range.