Abstract: A lubricating oil volume adjustment system and a lubricating oil volume adjustment method are provided. The system includes a storage device and a processor and is connected to a machine including a motor through a data acquisition device acquiring current information of the motor. The storage device stores a machine learning model trained by a training data set including a plurality of pieces of the current information of the motor during operation and a plurality of temperature values measured during operation of the machine. The processor is configured to acquire the current information of present operation of the motor by using the data acquisition device, predict a temperature value of the machine when the motor operates under the current information by using the machine learning model, and calculate and adjust a lubricating oil volume suitable to be used by the machine during operation according to the predicted temperature value.

Abstract: This disclosure provides a machine tool adjustment method and system thereof. The machine tool adjustment method includes the following steps: enabling a machine tool to perform a circular test; obtaining a measured error value Em from a measuring instrument, and the measured error value Em is defined by the difference between the actual circular trajectory and the preset circular trajectory during the circular test; determining an error condition of the tool machine from the measured error value Em; determining whether the error condition is less than a predetermined criteria; if not, defining a compensation parameter according to the error condition and enabling the machine tool to perform another circular test according to the set compensation parameter until the error condition is less than the predetermined criteria; and if yes, ending the circular test and the machine tool adjustment is finished.

Abstract: A lubricating oil volume adjustment system and a lubricating oil volume adjustment method are provided. The system includes a storage device and a processor and is connected to a machine including a motor through a data acquisition device acquiring current information of the motor. The storage device stores a machine learning model trained by a training data set including a plurality of pieces of the current information of the motor during operation and a plurality of temperature values measured during operation of the machine. The processor is configured to acquire the current information of present operation of the motor by using the data acquisition device, predict a temperature value of the machine when the motor operates under the current information by using the machine learning model, and calculate and adjust a lubricating oil volume suitable to be used by the machine during operation according to the predicted temperature value.

Abstract: This disclosure provides a machine tool adjustment method and system thereof. The machine tool adjustment method includes the following steps: enabling a machine tool to perform a circular test; obtaining a measured error value Em from a measuring instrument, and the measured error value Em is defined by the difference between the actual circular trajectory and the preset circular trajectory during the circular test; determining an error condition of the tool machine from the measured error value Em; determining whether the error condition is less than a predetermined criteria; if not, defining a compensation parameter according to the error condition and enabling the machine tool to perform another circular test according to the set compensation parameter until the error condition is less than the predetermined criteria; and if yes, ending the circular test and the machine tool adjustment is finished.