Key metrics for overall plant health using process data augmented with natural language processing from multiple sources.

Abstract

The method may include receiving binary data associated with one or more pieces of equipment in a manufacturing plant, the binary data indicating whether one or more performance variables associated with one or more pieces of equipment were outside a predetermined range; receiving text data associated with one or more pieces of equipment in a manufacturing plant; performing vectorization of the text data using natural language processing techniques to obtain vectorized data; receiving unplanned event data indicating unplanned events and associated pre-failure periods; and using the binary data, vectorized data, and unplanned event data to train a machine learning model to classify the state of the manufacturing plant between normal operating periods and pre-failure periods.

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