Methods and mechanisms for using machine learning to generate diagnostic reports based on anomalous data

Abstract

A system configured to detect, by a processing device, an anomaly that occurred during a manufacturing process performed by a substrate processing system. A set of prompts is generated based on the anomaly. Each prompt is correlated to specific data obtained from one or more datastores. For each prompt, a respective output of the first trained machine learning model is obtained and a structured prompt is generated based on respective outputs. The structured prompt is provided as input to a second trained machine learning model an output of the second trained machine learning model is obtained. The output of the second trained machine learning model comprising a diagnostic report associated with the anomaly.

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