Machine learning method and machine learning device for learning fault conditions, and fault prediction device and fault prediction system including the machine learning device

A machine learning device configured to learn a condition associated with a fault of an industrial machine, the machine learning device comprising:

• a memory;
• and
• at least one processor coupled to the memory, the at least one processor being configured to:
• while the industrial machine is in operation or at rest, obtain a state variable including at least one of
• output data from a sensor configured to detect a state of one of the industrial machine and a surrounding environment,
• internal data of control software controlling the industrial machine, and
• computational data obtained based on one of the output data and the internal data;
• obtain determination data indicating a fault of the industrial machine, and
• learn the condition associated with the fault of the industrial machine in accordance with a training data set including a combination of the state variable and the determination data, wherein
• the fault of the industrial machine is predicted in accordance with the learned condition, and
• the at least one processor is further configured to update the condition by weighting each of the determination data comprised in the training data set, in accordance with a length of time from when each of the determination data is obtained until the fault actually occurs.