Failure cause diagnostic device for injection molding machine
AssigneeFanuc Corporation
InventorJunpei Maruyama
Life of this patent
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Abstract
A failure cause diagnostic device of the present invention receives input of internal and external state data on injection molding machines and diagnoses failure cause of the injection molding machines by means of a machine learning device. An internal parameter of the machine learning device is obtained by performing machine learning using the state data obtained from the injection molding machines subject to failure cause and the state data obtained from the injection molding machines free of failure cause.
Claims12
A failure cause diagnostic device configured to determine a cause of failure of at least one injection molding machine, the device comprising a machine learning device configured to
- receive internal and external state data from the at least one injection molding machine, during a failure state and a non-failure state of the at least one injection molding machine,
- register a correlation among the internal and external state data in advance to identify primary and secondary causes of the failure state,
- perform machine learning on the internal and external state data to obtain an internal parameter of the machine learning device,
- set a state variable based on the internal and external state data at a predetermined time and a target variable based on a prediction of the failure state after a predetermined time period, and
- predict that the failure state of the injection molding machine occurs after the predetermined time period from the predetermined time.
A machine learning device configured to:
- receive internal and external state data from at least one injection molding machine, during a failure state and a non-failure state of the at least one injection molding machine;
- register a correlation among the internal and external state data in advance to identify primary and secondary causes of the failure state;
- perform the machine learning on the internal and external state data to obtain an internal parameter of the machine learning device;
- set a state variable based on the internal and external state data at a predetermined time and a target variable based on a prediction of the failure state after a predetermined time period;
- and
- predict that the failure state of the injection molding machine occurs after the predetermined time period from the predetermined time.
Dependencies are inferred from the claim text.