Industrial Assets Performance Labelling Based on Numerically Encoded Event Logs
Assessing the performance of industrial assets usually requires exploring and combining sensor data, event logs, asset characteristics and domain expert knowledge. Therefore, this process is time and resource consuming. We propose a methodology to label asset performances solely based on the event logs, using a standard (numerical) classifiers. The performance of a new asset operational cycle can then be assessed with negligible computational time.
Pierre is part of the Sirris EluciDATA team, working on predictive maintenance applied in an industrial context. Other topics of interests are performance analysis or production/consumption prediction of industrial assets.