Machining defect occurrence prediction system for machine tool

A defect occurrence prediction system of a machine tool which predicts an occurrence of a defective product in machined products by the machine tool, the defect occurrence prediction system comprising:

• an information data accumulation unit that accumulates various types of information and various types of data relating to a machining operation of the machine tool;
• a defective product occurrence information data extraction unit that extracts from the information data accumulation unit the various types of information and the various types of data when the defective product is produced in the machined products;
• and
• a defect occurrence prediction unit that performs a defect occurrence prediction on a basis of the various types of information and the various types of data extracted by the defective product occurrence information data extraction unit and various types of information and various types of data relating to a machining operation of the machine tool obtained in real time,
• wherein the various types of data include measurement data of at least one of a spindle motor and a servomotor during machining of the machine tool, and
• wherein the defect occurrence prediction unit is configured to predict a defect occurrence by performing statistical processing for the measurement data.

A defect occurrence prediction system of a machine tool which predicts an occurrence of a defective product in machined products by the machine tool, the defect occurrence prediction system comprising:

• an information data accumulation unit that accumulates various types of information and various types of data relating to a machining operation of the machine tool;
• a defective product occurrence information data extraction unit that extracts from the information data accumulation unit the various types of information and the various types of data when the defective product is produced in the machined products;
• and
• a defect occurrence prediction unit that performs a defect occurrence prediction on a basis of the various types of information and the various types of data extracted by the defective product occurrence information data extraction unit and various types of information and various types of data relating to a machining operation of the machine tool obtained in real time,
• wherein the various types of data include image data of at least one of a machined part and a tool during machining of the machine tool, and
• wherein the defect occurrence prediction unit is configured to predict a defect occurrence by using at least one of machine learning, threshold determination, and statistical processing on the image data.

A defect occurrence prediction system of a machine tool which predicts an occurrence of a defective product in machined products by the machine tool, the defect occurrence prediction system comprising:

• an information data accumulation unit that accumulates various types of information and various types of data relating to a machining operation of the machine tool;
• a defective product occurrence information data extraction unit that extracts from the information data accumulation unit the various types of information and the various types of data when the defective product is produced in the machined products;
• and
• a defect occurrence prediction unit that performs a defect occurrence prediction on a basis of the various types of information and the various types of data extracted by the defective product occurrence information data extraction unit and various types of information and various types of data relating to a machining operation of the machine tool obtained in real time,
• wherein the various types of data include measured data detected by an environmental sensor that measures, among air flow, temperature, humidity, pressure, illuminance, and air pollution which are environmental elements in a factory where the machine tool is installed, the environmental elements including at least the air flow, and
• wherein the defect occurrence prediction unit is configured to predict a defect occurrence by using at least one of machine learning, threshold determination, and statistical processing for the measurement data.