Design changes are unavoidable during mechanical product development; whereas the avalanche propagation of design change imposes severely negative impacts on the design cycle. To improve the validity of the change pro...Design changes are unavoidable during mechanical product development; whereas the avalanche propagation of design change imposes severely negative impacts on the design cycle. To improve the validity of the change propagation prediction, a mathematical program- ming model is presented to predict the change propagation impact quantitatively. As the foundation of change propa- gation prediction, a design change analysis model（DCAM） is built in the form of design property network. In DCAM, the connections of the design properties are identified as the design specification, which conform to the small-world network theory. To quantify the change propagation impact, change propagation intensity（CPI） is defined as a quantitative and much more objective assessment metric. According to the characteristics of DCAM, CPI is defined and indicated by tour assessment factors： propagation likelihood, node degree, long-chain linkage, and design margin. Furthermore, the optimal change propagation path is searched with the evolutionary ant colony optimiza- tion（ACO） algorithm, which corresponds to the minimized maximum of accumulated CPI. In practice, the change impact of a gear box is successfully analyzed. The pro- posed change propagation prediction method is verified tobe efficient and effective, which could provide different results according to various the initial changes.展开更多
基金Supported by Postdoctoral Science Foundation of China(Grant No.2015M572022)National Natural Science Foundation of China(Grant No.51505254)Distinguished Middle-Aged and Young Scientist Encourage and Reward Foundation of Shandong Province(Grant No.BS2015ZZ004)
文摘Design changes are unavoidable during mechanical product development; whereas the avalanche propagation of design change imposes severely negative impacts on the design cycle. To improve the validity of the change propagation prediction, a mathematical program- ming model is presented to predict the change propagation impact quantitatively. As the foundation of change propa- gation prediction, a design change analysis model（DCAM） is built in the form of design property network. In DCAM, the connections of the design properties are identified as the design specification, which conform to the small-world network theory. To quantify the change propagation impact, change propagation intensity（CPI） is defined as a quantitative and much more objective assessment metric. According to the characteristics of DCAM, CPI is defined and indicated by tour assessment factors： propagation likelihood, node degree, long-chain linkage, and design margin. Furthermore, the optimal change propagation path is searched with the evolutionary ant colony optimiza- tion（ACO） algorithm, which corresponds to the minimized maximum of accumulated CPI. In practice, the change impact of a gear box is successfully analyzed. The pro- posed change propagation prediction method is verified tobe efficient and effective, which could provide different results according to various the initial changes.
