基于粗糙集的柔性制造系统概念设计实例检索技术

摘要/Abstract

摘要： 针对柔性制造系统概念设计中的实例检索问题，提出了一种基于粗糙集理论的实例检索方法。分析了系统的需求特征和结构特征，通过建立属性决策表描述了实例信息；利用粗糙集理论对属性进行了重要性的判断和约简。为了处理属性表中的定量问题，给出了一种基于分级聚类法和决策属性支持度的离散化方法；抽取重要的特征属性作为检索依据，利用相似学方法进行相似度量，检索出最为接近的设计问题的实例作为设计参考。通过应用实例，给出了这种方法的具体实现过程。结果表明，该方法能够客观地反映实例与待求解问题的相似程度，保证了检索的正确性，提高了检索效率。

关键词: 柔性制造系统, 概念设计, 粗糙集理论

Abstract: A rough set-based case retrieval technology was presented in the conceptual design of Flexible Manufacturing Systems (FMS). Design cases were described as a decision table that was formed by demand features and configuration features of systems. Rough set theory was applied to calculate the important degree of each feature attribute and remove the redundant ones, then the most important features were selected to retrieve the most similar case in case database. And to deal with the quantitative features, a method using grade classification and decision attributes support degree were put forward. The proposed method was also demonstrated by an application example .The results objectively revealed the similarity degree between the new problem and similar case, and the veracity and efficiency of case retrieval has been improved.

Key words: flexible manufacturing system, conceptual design, rough set, case retrieval

中图分类号:

TH165

程晓冬，李建勇. 基于粗糙集的柔性制造系统概念设计实例检索技术[J]. .

CHENG Xiao-dong，LI Jian-yong. Rough set-based case retrieval technology in conceptual design of FMS[J]. .

参考文献

［1］ HEUNGSOON F L，KATHRYN E S. An integrated design support method for flexible manufacturing systems［J］. Journal of Manufacturing Systems, 1996,15(1)：73-84.

[2] ZHANG Guangqian, DENG Guishi. Prospect and technologies used in CBR［J］. Computer Engineering and Development, 2002,20(4)：52-55(in Chinese). ［张光前, 邓贵仕. 基于实例推理技术及其应用前景［J］. 计算机工程及应用, 2002,20(4)：52-55.］

[3] MAO Quan, XIAO Renbin, ZHOU Ji. Research on case-feature-based case indexing models in CBR［J］. Computer Research and Development, 1997,34(4)：257-263(in Chinese). ［毛权, 肖人彬, 周济. CBR中基于实例特征的相似实例检索模型研究［J］. 计算机应用与发展, 1997,34(4)：257-263.］

[4]ZHANG Wenxiu, WU Weizhi. Rough set theory and method［M］. Beijing: Science Press, 2001.32-40(in Chinese). ［张文修, 吴伟志. 粗糙集理论与方法［M］. 北京：科学出版社，2001.32-40.］

[5]RAO H A, PHAM S N, GU P. A genetic algorithms-based for design of manufacturing systems: an industrial application［J］. Intenational Joural Production Research, 1999,37(3)：557-580.

[6]DOUGHERRY J, KOHAVIR R, SAHAM M. Supervised and unsupervised discretization of continuous feathers［A］. Proceedings of the 12th Intenational. Confrence on Machine Learning［C］.San Francisco, CA, USA: Morgan Kaufmann Publishers, 1995.194-202.

[7]ZHOU Meili. Similarity engineering［M］. Beijing: China Machine Press, 1998.75-152(in Chinese).［周美立. 相似工程学［M］.北京: 机械工业出版社, 1998.75-152.］

[8]ZHANG Genbao. Automatic manufacturing systems［M］. Beijing: China Machine Press, 2000.99-108(in Chinese).［张根保.自动化制造系统［M］. 北京: 机械工业出版社,2000.99-108.］

[1]	王宏刚,王姗姗,姚佳,潘若禹,庞胜利. 基于邻域粗糙集与支持向量机的射频识别系统识别率预测[J]. 计算机集成制造系统, 2019, 25(12): 3170-3180.
[2]	杨续昌,陈友玲,刘传彪. 云制造环境下员工资源选择方法[J]. 计算机集成制造系统, 2018, 24(第3): 711-719.
[3]	袁琳,刘玉生. 基于SysML的概念设计功能建模方法[J]. 计算机集成制造系统, 2018, 24(第1): 164-177.
[4]	李玉良,林培何. 复杂产品的并行变更传播模型研究[J]. 计算机集成制造系统, 2017, 23(第4期): 737-743.
[5]	宫琳,张子健,谢剑,阎艳. 融合设计过程与设计知识的产品概念设计方法[J]. 计算机集成制造系统, 2016, 22(第3期): 597-610.
[6]	杨琨,李彦,熊艳,李文强,那惠珍. 基于复杂网络的知识驱动产品创新设计[J]. 计算机集成制造系统, 2015, 21(第9期): 2257-2269.
[7]	杨涛,杨育,张雪峰,于国栋,薛承梦. 基于客户聚类分析的产品概念设计方案评价决策方法[J]. 计算机集成制造系统, 2015, 21(第7期): 1669-1678.
[8]	杨涛,杨育,张东东. 考虑客户需求偏好的产品创新概念设计方案生成[J]. 计算机集成制造系统, 2015, 21(第4期): 875-884.
[9]	王占松,田凌,段文睿. 基于设计意图建模的知识推送技术[J]. 计算机集成制造系统, 2015, 21(第3期): 606-617.
[10]	刘泽林,钱仲焱,陈泳. 基于概念图的民机概念设计要求识别与获取[J]. 计算机集成制造系统, 2015, 21(第10期): 2549-2557.
[11]	姜莉莉,李彦,李文强,熊艳. 基于多视角的产品概念设计表达模型[J]. 计算机集成制造系统, 2014, 20(5): 989-.
[12]	杨波,高常青,王兴祖,姚孔,尹晓玲. 基于单元模型的产品结构概念设计[J]. 计算机集成制造系统, 2014, 20(3): 471-.
[13]	康与云,唐敦兵. 基于矩阵的多功能产品概念方案求解方法[J]. 计算机集成制造系统, 2014, 20(12): 2915-2925.
[14]	闫明明,赵咪. S3PR网的一种最大许可活性监督控制器设计方法[J]. 计算机集成制造系统, 2013, 19(07 ): 1548-1552.
[15]	张建辉，檀润华，张鹏，曹国忠. 计算机辅助创新驱动的产品概念设计创新设想产生过程模型[J]. , 2013, 19 (02 ): 0-0.