FRAMEWORK FOR A DISTRIBUTED AND HYBRID PROGNOSTIC SYSTEM

The purpose of this paper is to define a framework for the implantation of a distributed, adaptable and open prognostic system able to take into account, on one hand, the dynamic of the monitored equipment and, on the other hand, the evolution of performance criteria. In this way, the prognostic process is (re)defined: at the component level and at the global level of the system (whole equipment). In the distributed model proposed, the interest of neural networks as “prognostic tools” is pointed out. The work is in coherence with actual industrial maintenance developments like “e-maintenance systems” or “web-services applications”.