Leading indicator for overall plant health using process data augmented with natural language processing from multiple sources

A computing device comprising a processor configured to:

• receive 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 the one or more pieces of equipment were outside of a predetermined range;
• receive text data associated with the one or more pieces of equipment in the manufacturing plant;
• perform a vectorization of the text data using natural language processing techniques to obtain vectorized data;
• receive unplanned event data indicating unplanned events and associated pre-failure periods;
• and
• use the binary data, the vectorized data, and the unplanned event data to train a machine learning model to classify a state of the manufacturing plant between a normal operating period and a pre-failure period.

A system comprising:

• one or more of pieces of equipment in a manufacturing plant;
• and
• a computing device comprising a processor configured to:
• receive binary data associated with one or more pieces of equipment in the manufacturing plant, the binary data indicating whether one or more performance variables associated with the one or more pieces of equipment were outside of a predetermined range;
• receive text data associated with the one or more pieces of equipment in the manufacturing plant;
• perform a vectorization of the text data using natural language processing techniques to obtain vectorized data;
• receive unplanned event data indicating unplanned events and associated pre-failure periods;
• and
• use the binary data, the vectorized data, and the unplanned event data to train a machine learning model to classify a state of the manufacturing plant between a normal operating period and a pre-failure period.