云制造模式下采用Rough-ANP的机械设计知识优选推送策略

李雪瑞; 余隋怀; 初建杰

doi:10.13433/j.cnki.1003-8728.20180181

云制造模式下采用Rough-ANP的机械设计知识优选推送策略

doi: 10.13433/j.cnki.1003-8728.20180181

1.
西北工业大学陕西省工业设计工程实验室, 西安 710072

基金项目:

国家重点研发专项课题项目（2017YFB1104205）与国家科技支撑计划项目（2015BAH21F01）资助

详细信息

作者简介:
李雪瑞(1988-),博士研究生,研究方向为产品创新设计、知识管理等,lxr0829@mail.nwpu.edu.cn

通讯作者:
初建杰,副教授,博士,cjj@nwpu.edu.cn

计量
- 文章访问数: 305
- HTML全文浏览量: 33
- PDF下载量: 111
- 被引次数: 0
出版历程
- 收稿日期: 2017-12-25
- 刊出日期: 2018-09-05

Optimal Selection Strategy of Mechanical Design Knowledge via Rough-anp in Cloud Manufacturing Environment

1.
Shaanxi Engineering Laboratory for Industrial Design, Northwestern Polytechnical University, Xi'an 710072, China

摘要

摘要: 合理应用机械设计知识可以辅助提升创新设计的效率和质量。本文立足于云模式下的机械设计过程，提出基于行为-结构-知识的机械设计知识解构模型；提出一种云制造模式下基于Rough-ANP的机械设计知识优选推送策略，该方法充分结合了粗糙集理论（Rough set theory）在处理模糊性和不确定性方面的优势以及网络层次分析法（ANP）在处理多目标评估问题的优势。最后以电动铲运机设计为案例，验证了该机械设计知识优选推送策略的有效性。
- 设计知识 /
- 知识优选 /
- 粗糙集 /
- 网络层次分析法
Abstract: Reasonable application of mechanical design knowledge can help improve the efficiency and quality of innovative design. The proposal based on the mechanical design process in cloud manufacturing, a deconstructive approach of design knowledge based on the behavior-structure-knowledge model is provided. And then, in this paper a novel optimal selection strategy of mechanical design knowledge based on Rough-ANP is proposed. The novel approach makes use of the strength of rough set theory in handling vagueness and uncertainty and the superiority of analytic network process (ANP) in non-independent hierarchy evaluation. Finally, a case is presented to demonstrate the effective auxiliary function of the novel approach.
- design knowledge /
- optimal selection of knowledge /
- rough set theory /
- analytic network process

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参考文献(14)

[1]	Wu H, Xu L D. A state-of-the-art survey of cloud manufacturing[J]. International Journal of Computer Integrated Manufacturing, 2015,28(3):239-250
[2]	阴艳超,丁卫刚,吴磊.基于不确定规则推理的云制造知识服务方法[J].计算机集成制造系统,2015,21(4):1114-1123 Yi Y C, Ding W G, Wu L. Knowledge service method of cloud manufacturing based on uncertain rule reasoning[J]. Computer Integrated Manufacturing Systems, 2015,21(4):1114-1123(in Chinese)
[3]	Park J. Developing a knowledge management system for storing and using the design knowledge acquired in the process of a user-centered design of the next generation information appliances[J]. Design Studies, 2011,32(5):482-513
[4]	Matta N, Ducellier G, Djaiz C. Traceability and structuring of cooperative knowledge in design using PLM[J]. Knowledge Management Research & Practice, 2013,11(1):53-61
[5]	梁野,张树有,刘晓健,等.基于变权分层激活扩散模型的产品设计知识动态推送技术[J].计算机集成制造系统,2015,21(12):3107-3118 Liang Y, Zhang S Y, Liu X J, et al. Product design knowledge dynamic push technology based on variable-weight layered spreading activation model[J]. Computer Integrated Manufacturing Systems, 2015,21(12):3107-3118(in Chinese)
[6]	赵楠,牛占文,郭伟.云制造环境中面向设计知识资源序列化组合的量子和声搜索算法[J].计算机集成制造系统,2012,18(7):1435-1443 Zhao N, Niu Z W, Guo W. Quantum harmony search method for design knowledge resource serialization combination in cloud manufacturing environment[J]. Computer Integrated Manufacturing Systems, 2012,18(7):1435-1443(in Chinese)
[7]	Qu M, Yu S H, Chen D K, et al. An improved rough set approach to evaluate auto-mobility systems[J]. Journal of Intelligent & Fuzzy Systems, 2017,33(3):1339-1353
[8]	Kumru M, Kumru P Y. A fuzzy ANP model for the selection of 3D coordinate-measuring machine[J]. Journal of Intelligent Manufacturing, 2015,26(5):999-1010
[9]	Gero J S. Design prototypes:a knowledge representation schema for design[J]. Ai Magazine, 1990,11(4):26-36
[10]	Christophe F, Bernard A, Coatanéa É. RFBS:a model for knowledge representation of conceptual design[J]. CIRP Annals, 2010,59(1):155-158
[11]	Chen X L, Lou P H, Tang D B, et al. Behavior-function & behavior-structure hybrid mappings in mechanical conceptual design[J]. Computer Integrated Manufacturing Systems, 2010,16(7):1363-1370
[12]	陈继文,杨红娟,张进生,等.基于变型空间FBS本体映射的产品创新设计方法[J].计算机集成制造系统,2013,19(11):2671-2679 Chen J W, Yang H J, Zhang J S, et al. Product innovative design based on variant space FBS ontology mapping[J]. Computer Integrated Manufacturing Systems, 2013,19(11):2671-2679(in Chinese)
[13]	Pawlak Z. Rough set theory and its applications[J]. Journal of Telecommunications and Information Technology, 2002:7-10
[14]	Zhai L Y, Khoo L P, Zhong Z W. Design concept evaluation in product development using rough sets and grey relation analysis[J]. Expert Systems with Applications, 2009,36(3):7072-7079