Systems and methods for monitoring and controlling industrial processes

A system comprising:

• a non-transitory computer-readable medium storing instructions;
• and
• a processing device communicatively coupled to the non-transitory computer-readable medium, wherein the processing device is configured to execute the instructions and thereby perform operations comprising:
• determining temperature data for at least part of an article of manufacture in a manufacturing process;
• analyzing the temperature data to identify a first portion of the article of manufacture having a temperature that deviates from a surrounding portion of the first portion, the first portion comprising:
• at least one hot spot, at least one hot streak, at least one cold spot, or at least one cold streak on the article of manufacture;
• determining, for the first portion of the article of manufacture, a set of properties comprising one or more of:
• a temperature of the first portion of the article of manufacture;
• or
• a material type of the article of manufacture;
• processing the set of properties for the first portion of the article of manufacture using at least one of a rules-based model, a machine-learning model, or a classification model to produce a defect classification for the first portion of the article of manufacture, the defect classification comprising an identification of a contaminant in the article of manufacture having a thermal property that differs from a thermal property of the article of manufacture;
• and
• providing an indication of the defect classification for display on a computing device;
• and
• providing the defect classification to at least one of a second machine-learning model or a second rules-based model to cause the second machine-learning model or the second rules-based model to generate a prediction as to an occurrence of a breakage event on the first portion of the article of manufacture based on the defect classification.

A computer-implemented data processing method for identifying and classifying potential defects in an article of manufacture, the method comprising:

• determining temperature data from thermal imaging data for at least part of an article of manufacture in a manufacturing process;
• analyzing, by computing hardware, the temperature data to identify a first portion of the article of manufacture having a temperature that deviates from an expected temperature;
• determining, by the computing hardware for the first portion of the article of manufacture, a set of properties for the first portion of the article of manufacture, the set of properties comprising one or more of:
• location data for the first portion of the article of manufacture with respect to the article of manufacture;
• an absolute temperature of the article of manufacture;
• a shape of the first portion of the article of manufacture;
• or
• a temperature deviation of the first portion with respect to the expected temperature;
• processing, by the computing hardware, the set of properties for the first portion of the article of manufacture using at least one of a rules-based model, a machine-learning model, or a classification model to produce a defect classification for the first portion of the article of manufacture;
• providing, by the computing hardware, an indication of the defect classification for display on a computing device;
• providing, by the computing hardware, the defect classification to at least one of a second machine-learning model or a second rules-based model to cause the second machine-learning model or the second rules-based model to generate a prediction as to an occurrence of a breakage event on the first portion of the article of manufacture based on the defect classification.