REVIEWING AN INTEGRATED APPROACH OF PRODUCT DESIGN STRUCTURE MATRIX (DSM) AND FUZZY SET THEORY (FST) TO CLUSTERING COMPLEX PRODUCT
The purpose of this paper is to present an integrated approach to the design of structure matrix and fuzzy set theory; and also to provide a method for clustering the system elements. In this approach, know as the \fuzzy design structure matrix", integer numbers are replaced by fuzzy numbers. In fact, one of the problems of designing structure matrix analysis using numbers integer, considering the lack of distinction between the dependence of the interactions of system elements is that such problemswillbesolvedwiththisapproach. Ontheother hand, the fuzzy design structure matrix of interactions between elements, cost and less time is spent on systems analysis. According to the literature, there are dierent methods for clustering system elements. By studying the clustering methods as well as mathematical approaches derived from graph theory, a proposed approach for clustering fuzzy design structure matrix was presented. The proposed approach has ve major steps. Each step also includes several subsets. In the rst step, the elements are identied with inputs from designers and system boundaries are determined. In the second step, the fuzzy numbers are used in fuzzy evaluation method. In the third step, the basic fuzzy design structure matrix is formed. In the next step, the grouping proposed for clustering fuzzydesignstructurematrixis presented. Finally,using the matrix of hierarchical relationships, priorities and the importance of clusters are determined. Analytical Network Process (ANP) is used for fuzzy evaluation method. In the literature related to the design structure matrix in this case, the Analytical Hierarchy Process (AHP) has been used. considering the AHP hierarchy, some of interactions between elements have been ignored. Therefore, this shortage has been resolved by the ANP and the interactions between the elementshavebeenconsideredandevaluatedwithhigher accuracy. The proposed approach has been implemented on a servomechanism with two degrees of freedom. The system has 15 elements determined by the designers. By implementing this approach, two independent elements and three clusters have been determined.
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