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

Abstract

Abstract: 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.

Key words: data-driven decision-making； technique for order preference by similarity to an ideal solution(TOPSIS)； entropy method； Borda function, product design scheme

摘要：

目前产品设计方案的优劣主要依赖于设计者的经验和水平。提出了一种数据驱动的产品设计方案多属性决策方法，可以应用于产品设计各个阶段的方案评估择优。每一组评审者应用理想解排序方法对方案进行评估，对于决策准则的权重，采用熵权法确定其权值，应用Borda函数法对各组人员的决策进行集结，得到最终的决策结果，完成对设计方案的综合评估。该方法对数据的使用更加充分，最大程度避免了主观性，评价结果更为合理。最后，将该方法应用于油田聚合物注入装置的设计方案择优，集结了设计、工艺、管理人员的意见，提供了更为全面的优化决策结果。

关键词: 数据驱动决策, 逼近理想解的排序法, 熵法, 波达函数, 产品设计方案

CLC Number:

TH16
TP391

WU Yangdong, ZHANG Taihua, LIU Dan, WANG Yiquan. Data-driven Multi-attribute Optimization Decision-making for Complex Product Design Schemes[J]. China Mechanical Engineering.

吴扬东, 张太华, 刘丹, 王宜全. [数据驱动的产品设计]复杂产品设计方案的数据驱动多属性优化决策[J]. 中国机械工程.

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