Diagnosis in complex system with multiple failure sources

International audienceThis paper proposes an approach to accurately localize the origin of product quality drifts, in a flexible manufacturing system (FMS). The failure propagation mechanism in a production process is proposed based on the relationships between failure sources to explain the failure propagation following production flow. The logical diagnosis model is used to reduce the search space of suspected equipment in the production flow; however, it does not help in accurately localizing the faulty equipment. In the proposed approach, we model this reduced search space as a Bayesian network that uses historical data to compute conditional probabilities for each suspected equipment. This approach helps in making accurate decisions on localizing the cause for product quality drifts as either one of the equipment in production flow or product itself