The multiple reconfiguration and the complexity of the modern production system lead to design intelligent monitoring aid systems. Accordingly, the use of neurofuzzy technics seems very promising. In this paper, we propose a new monitoring aid system composed by a dynamic neural network detection tool and a neuro-fuzzy diagnosis tool. Learning capabilities due to the neural structure permit us to update the monitoring aid system. The neuro-fuzzy network provides an abductive diagnosis. Moreover it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. At the end, we illustrate the industrial usefulness of the proposed dynamic neuro-fuzzy monitoring system trough a flexible production system monitoring application. Key words: UML, neural network, neuro-fuzzy, diagnosis, monitoring, maintenance, SCADA, CMMS, FMECA, fault tree. PACS: 07.05.Mh, 87.57.Ra
N. Palluat, Daniel I. Racoceanu, Noureddine Zerhou