System and method for controlling semiconductor manufacturing apparatus

A system for controlling a semiconductor manufacturing apparatus comprising:

• a sensor unit capturing a set of data related to a health status of the semiconductor manufacturing apparatus;
• a sensor interface receiving the set of data and generating at least one input signal or a database server;
• one or more processors;
• and
• one or more computer-readable non-transitory storage media coupled to the one or more processors and comprising instructions operable when executed by the one or more processors to cause the control system to:
• receive the at least one input signal from the database server and performing a front end process to generate a first data signal;
• perform a health status monitoring process to determine whether a malfunction has occurred in the semiconductor apparatus and to generate a second data signal;
• perform an artificial intelligence (AI) analytical process to generate an output signal according to the second data signal;
• perform the AI analytical process by further utilizing a statistical model prediction including a deep learning model to obtain an apparatus lifetime prediction score of the semiconductor manufacturing apparatus corresponding to the set of data related to the health status in the first data signal;
• identifying and categorizing, with the statistical model prediction, the second data signal into a matching trend group and a non-matching trend group;
• and
• generate an alert signal and a feedback signal according to the output signal, and transmit the alert signal to a user of the semiconductor manufacturing apparatus.

A method for controlling a semiconductor manufacturing apparatus comprising:

• capturing, by a sensor unit, a set of data related to a health status of the semiconductor manufacturing apparatus;
• receiving, by a sensor interface the set of data and generating at least one input signal for a database server;
• receiving, by a front end subsystem, the at least one input signal from the database server and performing a front end process to generate a first data signal;
• receiving, by a diagnosis subsystem, the first data signal from the front end subsystem and performing a health status monitoring process to determine whether a malfunction has occurred in the semiconductor manufacturing apparatus and to generate a second data signal;
• performing, by a decision subsystem, an artificial intelligence (AI) analytical process to generate an output signal according to the second data signal from the diagnosis subsystem;
• performing, by the decision subsystem, the AI analytical process to utilize a statistical model prediction including a deep learning model to obtain an apparatus lifetime prediction score of the semiconductor manufacturing apparatus corresponding to the set of data related to the health status in the first data signal;
• identifying and categorizing, with the statistical model prediction, the second data signal into a matching trend group and a non-matching trend group;
• and
• generating, by a message and feedback subsystem, an alert signal and a feedback signal according to the output signal and transmitting the alert signal to a user of the semiconductor manufacturing apparatus.