计算机集成制造系统 ›› 2015, Vol. 21 ›› Issue (第3期): 634-647.DOI: 10.13196/j.cims.2015.03.008

• 产品创新开发技术 • 上一篇    下一篇

基于FCM和IGA的广义客户需求分析及其资源配置

谢建中1,2,杨育1,张晓微1,李斐1,康国旭1   

  1. 1.重庆大学机械传动国家重点实验室
    2.富士康科技集团
  • 出版日期:2015-03-31 发布日期:2015-03-31
  • 基金资助:
    国家自然科学基金资助项目(71071173;贵州省科学技术支撑计划资助项目(2012GZ98743)。

Generalized customer requirement and it's resource allocation based on FCM and IGA

  • Online:2015-03-31 Published:2015-03-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71071173),and the Guizhou Provincial Key Technology R&D Program,China(No.2012GZ98743).

摘要: 针对需求分析中的长鞭效应及模糊性和不确定性问题,提出了面向产品全生命周期管理的广义客户需求分析方法,该方法首先在产品生命周期管理全集内采集客户需求,在此基础上抽取客户隐性需求,构建基于模糊认知图的广义客户需求分析模型,并采用免疫遗传算法对模糊认知图中的广义客户需求进行相关性分析;对广义客户需求及企业资源进行统一的模糊度量,构建面向产品生命周期管理的需求向资源映射的配置优化模型,并从中选择与客户需求有关的资源,实现质量屋中广义客户需求向企业资源映射的自动配置决策,从而建立一种资源对需求满足间的反馈机制;以某制造企业为实例,应用MATLAB工具箱进行仿真研究,验证了所提方法和模型的正确性与有效性。

关键词: 产品全生命周期管理, 广义客户需求, 隐性需求, 模糊质量屋, 知识挖掘

Abstract: To deal with the fuzziness and the uncertain problems in customer requirement analysis,an analysis method of generalized customer requirement facing Product Lifecycle Management(PLM)was put forward.The customer requirement in PLM set was collected and the implicit demands from customers were extracted on this basis.The generalized customer demands analysis model based on Fuzzy Cognitive Map(FCM)was constructed,and the correlation among the demands was analyzed by immune genetic algorithm.The configuration optimization model of fuzzy house of quality was constructed,and related resources were selected to realize automatic allocation decision from the generalized customer requirement to enterprise resources mapping in the house of quality.Thus a feedback mechanism between resources and the customer demands was established.A case study of manufacturing company was provided to illustrate the validity and feasibility by means of Matlab tool.

Key words: product lifecycle management, generalized customer requirement, implicit demands, fuzzy house of quality, knowledge mining

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