Affiliation:
1. College of Mechanical Engineering and State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China
2. College of Mechanical Engineering, Chongqing University of Arts and Sciences, Chongqing, China
Abstract
Due to the existence of coupling relationships, quality characteristics form a variation propagation process, which increases the risk possibility of product quality. In order to improve the robustness of quality characteristics, this paper proposes a fuzzy clustering-based key quality characteristics decoupling planning considering risk criticality. Firstly, based on the design structure matrix, a modular correlation matrix of key quality characteristics was established to quantify the coupling relationships among them. Secondly, according to the variation characteristics of quality characteristics, the variation propagation model is constructed to identify the potential quality risk. Thirdly, the fuzzy clustering algorithm is used to obtain the optimal control sequence of key quality characteristics. Finally, the computerized numerical control machine tool is taken as an actual case, the effectiveness and superiority of this method are verified by the comparison of the numerical result and method. This method provides a new indicator system solution for the coupling analysis of product design.
Cited by
3 articles.
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