Knowledge component-based intelligent method for fixture design

Abstract

Aiming at providing an effective mechanism for representation, organization, and reuse of fixture design knowledge, this paper puts forward an intelligent methodology for fixture design based on knowledge component technology. First, the ontology models of fixture elements, the workpiece, and the fixture design case are constructed to organize the statical design knowledge related to each of them. Then, the fixture design process-related knowledge is modeled by knowledge components corresponding to fixture layout planning process and fixture structure design process. Hence, the hierarchy structure of the fixture design knowledge reuse is formed. Under the framework of the fixture layout knowledge component, the association analysis method is used for generating reasoning rules and then the rule-based reasoning (RBR) method is used for the determination of the workpiece-locating mode and the initiative candidate of the locating datum. Further, an entropy weight fuzzy comprehensive evaluation method is employed to select the most suitable locating datum from the candidates. Under the framework of the fixture structure design knowledge component, the selection of fixture elements, element dimension drive, and auto-assemble are fulfilled by the combination of RBR and case-based reasoning (CBR). The method realizes the effective organization and efficient use of fixture design knowledge and improves the efficiency of fixture design. It has been verified by a case of airplane part machining fixture design.