Implementing Machine Learning Microservices for Predictive Maintenance of Industrial Assets

In this work, conducted by three partners — UFAM/CETELI, INDT, and Envision (TPV Group) — we present a system comprising machine learning microservices for predicting defects in industrial assets at the ENVISION factory. Data collected through sensors installed in the factory’s industrial assets are processed by machine learning models to generate predictions of failures and machine stops, which are then displayed to the user through a front end.