Data-driven Multi-attribute Optimization Decision-making for Complex Product Design Schemes

被引：1
|
作者：
Wu Y. [1 ]
Zhang T. [2 ]
Liu D. [1 ]
Wang Y. [1 ]
机构：
[1] Key Laboratory of Modern Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang
[2] College of Mechanical and Electrical Engineering, Guizhou Normal University, Guiyang
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2020年 / 31卷 / 07期
关键词：
Borda function; Data-driven decision-making; Entropy method; Product design scheme; Technique for order preference by similarity to an ideal solution(TOPSIS);
D O I：
10.3969/j.issn.1004-132X.2020.07.012
中图分类号：
学科分类号：
摘要：
At present, the quality of product design scheme mainly depended on the experiences and levels of designers, to solve this problem, a data-driven multi-attribute decision-making method for product design schemes was proposed, which might be applied to the evaluation of the best program at all stages of product design. Each group of reviewers used the TOPSIS method to evaluate the scheme, for the weight of decision criteria, the entropy weight method was used to determine the weights, the Borda function method was applied to assemble the decisions of each group, the final decision results were obtained, and the comprehensive evaluations of the design scheme were completed. This method was more fully used for data, avoiding subjectivity to the greatest extent, and the evaluation results were more reasonable. Finally, the method was applied to the design of oilfield polymer injection devices, and the opinions of designers, processors and managers are gathered to provide more comprehensive optimization decision results. © 2020, China Mechanical Engineering Magazine Office. All right reserved.
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页码：865 / 870
页数：5
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