DIAPASE: an industrial diagnosis tool by knowledge based approach for an agro-alimentary production system

The search for an increase in quality and speed of the diagnosis led to the reduction in the unavailability times of the production equipment. Thus, among the objectives of this study, need for operating on the level of the industrial sector of production through making of tools of assistance to the diagnosis of the abnormal operations, which are integrated into the environment of the system and allow the optimization of intervention times. The various problems encountered by the teams of control and maintenance and formed very well concern the complexity of the equipment, in more of the reasoning of diagnosis, which is often rather complex and frequently rests on strategies making it possible to guide search concerned with the human expertise. A data-processing help is justified and expert system approaches it answers its requirements fully. Our study aims to contribute to propose a tool for operators' assistance in their tasks of diagnosis of the problems occurring on the level of an industrial process and the assistance to their resolution. For the realization of this study, the choice was made be based on the one hand on the techniques of the artificial intelligence, more precisely the approach system containing knowledge and on the other hand on the techniques of functional and material modeling. In this paper, we would initially analyze the context in which must be integrated the system of assistance into the diagnosis, then we would develop the methodological aspects which make it possible to work out a solution which answers the needs and constraints of the exploitation of the process in which we are interested.