标题:Design Property Network-Based Change Propagation Prediction Approach for Mechanical Product Development
作者:Ma, Songhua; Jiang, Zhaoliang; Liu, Wenping; Huang, Chuanzhen
作者机构:[Ma, S] Key Laboratory of High Efficiency and Clean Mechanical Manufacture of Ministry of Education, Shandong University, Jinan, 250061, China;[ Jiang 更多
通讯作者:Ma, Songhua
通讯作者地址:[Ma, SH]Shandong Univ, Key Lab High Efficiency & Clean Mech Manufacture, Minist Educ, Jinan 250061, Peoples R China.
来源:中国机械工程学报
出版年:2017
卷:30
期:3
页码:676-688
DOI:10.1007/s10033-017-0099-z
关键词:Change propagation prediction;Small-world network;Change propagation intensity(CPI);Design change analysis model(DCAM);Ant colony optimization(ACO)
摘要: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 programming model is presented to predict the change propagation impact quantitatively.As the foundation of change propagation 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 four 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 optimization(ACO) algorithm,which corresponds to the minimized maximum of accumulated CPI.In practice,the change impact of a gear box is successfully analyzed.The proposed change propagation prediction method is verified to be efficient and effective,which could provide different results according to various the initial changes.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026552680&doi=10.1007%2fs10033-017-0099-z&partnerID=40&md5=86fa199e24e2068d6dcbc782ed43ecd0
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