An application of multi-criteria decision aids models for Case-Based Reasoning

Industrial decision-makers often try to develop new products by reusing their past experience. Methods for obtaining feedback are available in knowledge management and produce tangible results in the industrial world. Nowadays, companies often consider employees’ knowledge as an asset. This approach is a potential answer for reusing knowledge acquired through experience. The Case-Based Reasoning (CBR) methodology, based on cognitive sciences, consists in solving new problems by reusing past experience. Case-Based Reasoning is an approach to solving a new problem by remembering and adapting a previous successful similar situation to the problem at hand. Of the four activities comprising CBR – Retrieve, Reuse, Revise, and Retain-this paper deals with the “Retrieve” phase. Consequently, we suggest using the Multi-Criteria Decisions concept in problem description to search for the solution in a case-based scenario. We show that Multi-Criteria Decisions and Case-Based Reasoning are complementary. This paper proposes using knowledge acquisition as a basis for seeking solutions from non-compensatory multi-criteria decision aids such as the ELECTRE-I and ELECTRE-II methods. We also carry out a robustness analysis at the end of this paper. We describe an industrial application with wire forming machines as an illustration of our recommendation.