Decision-making in self-reconfiguration of a knowledgeable manufacturing system

This paper presents the two decision-making methods for reconfiguring knowledge meshes (KMs) and selecting the best from several reconfigured KMs in the self-reconfiguration of a knowledgeable manufacturing system (KMS). Based on the fuzzy requirement relationships for KMs, the operations on fuzzy requirement degrees for KMs are defined and the requirement evaluation method for the KM is proposed together with its decision-making method, which is used for the KM reconfiguration. Next, a grey decision-making tree method is proposed to select the best from several reconfigured KMs. First, the factors influencing the decision-making on the selection of reconfigured KMs are analysed. Then, the conceptual model of decision-making factors is given, and the factors are evaluated by various methods such as investigation, evaluation, and functional analysis. On the basis of relational analysis, the grey decision-making tree model is proposed, and the detailed decision-making steps are provided. Finally, the KM reconfiguration and the reconfigured-KM selection are exemplified. The decision-making result fully indicates that the methods can effectively solve the decision-making problem in the KMS self-reconfiguration.