1. Intelligent predictive maintenance for Industry 4.0

Gilles ZWINGELSTEIN: Engineer, École nationale supérieure d'électrotechnique, d'électronique, d'informatique, d'hydraulique et des télécommunications de Toulouse (ENSEEIHT), Doctor of Engineering, Doctor of Science, retired Associate Professor, Université Paris-Est Créteil, France.

Predicting equipment failure is a major concern for maintenance managers, in order to define the most technically and economically relevant strategies. The spread of new digital technologies has led to the development of intelligent predictive maintenance for Industry 4.0. It should be emphasized that the level of predictive confidence depends predominantly on the volume of data relating to a single failure, not to mention in-depth knowledge of the physical mechanisms of degradation....