Explainable Decision Support Tool for IoT Predictive Maintenance within the context of Industry 4.0
Résumé
This paper proposes a decision support tool that combines both prediction and explanation capacities in order to perform the predictive maintenance. The proposed decision support tool provides explanations about a degradation occurrence and its dynamic development based on the domain expertise knowledge as well as the exploitation of sensor data and inspection reports. The proposed tool is illustrated using a well-known C-MAPSS (Commercial Modular Aero-Propulsion System Simulation) data competition benchmark simulating the degradation of a fleet of gas-turbine engines.