Over the past twenty years, the maintenance function has undergone considerable change to respond to advanced technologies of information and communication (NTIC) with successive concepts, emaintenance and s-maintenance. The important role of the human factor in the problems related to conduct industrial processes is indisputable and is justified by a greater diversity of research. Indeed, the consideration of the human characteristics is essential to enhance the factory performance. Particularly, reuse of human knowledge is an element which plays an essential role in the continuous improvement of maintenance activities. In this context, we are interested to the problem of selection of experts in maintenance process. We propose, in this paper, a new approach to formalize knowledge as first step to solve the experts' selection problem under the previous experience. In that purpose, this paper takes domain ontology as a framework, the experience feedback models used to select experts, in the purpose to collaborate the interactions between them as a team that is capable of making decision in a fault diagnosis/repair situation based not only on skills but also according to the previous experience and CMDO ontology as the knowledge domain.

No abstract

Knowledge management (KM) is a familiar concept to specialists in information and documentation. Tacit knowledge and explicit knowledge are often communicated with difficulty acquired by experience or learning. In industrial systems and precisely in a maintenance system, it has a wealth of knowledge often poorly exploited especially during the execution of the maintenance process also the establishment of a network or intranet or document circulation system which poses problems of integration and data exchange. As a model to express the semantic data, ontologies are one of the solutions to these relevant problems. The aim is to propose an approach to capitalize the knowledge; it is based on capitalization, especially the skills of experts. We propose in this paper to present in the first place, the effectiveness of the capitalization of knowledge in the field of maintenance. Then we propose an approach to build a knowledge base based on ontology.

No abstract