• 论文 •    

基于灰色系统理论的质量屋中动态需求的分析与预测

李中凯,冯毅雄,谭建荣,方辉,   

  1. 1.浙江大学 流体传动及控制国家重点实验室,浙江杭州310027;2.中国矿业大学 机电工程学院,江苏徐州221116;3.四川大学 制造科学与工程学院,四川成都610065
  • 出版日期:2009-11-15 发布日期:2009-11-25

Analysis and prediction for dynamic requirements in house of quality based on grey theory

LI Zhong-kai,FENG Yi-xiong, TAN Jian-rong,FANG Hui,   

  1. 1.State key Lab of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027,China;2.School of Mechatronics Engineering, China University of Mining & Technology, Xuzhou 221116, China;3.School of Manufacturing Scinece & Engineering, Sichuan University, Chengdu 610065, China
  • Online:2009-11-15 Published:2009-11-25

摘要: 针对质量功能配置中需求重要度分析方法的不足,提出了多属性决策与趋势预测集成的质量屋动态需求分析方法。通过分析需求信息的模糊性、个性化和阶段多变性等动态特征,将灰色系统理论引入需求处理过程,以数据获取、多属性决策和趋势预测为基本模块,构建了质量屋动态需求分析与预测的集成模型。将客户和市场竞争因素调查作为数据源,完成基础数据采集,引入灰关联度分析方法,进行客户需求和技术需求重要度分析,运用GM(1,1)模型获取需求重要度的近期发展趋势知识,实现质量功能配置中需求信息的采集、分析和预测。最后,以大型空分成套装备的需求分析为例,验证了该方法的可行性和有效性。

关键词: 质量功能配置, 灰色系统理论, 灰关联度分析, 趋势预测, 多属性决策

Abstract: Aiming at the deficiencies of requirements'importance analysis in Quality Function Deployment (QFD), a dynamic requirements'analysis method in house of quality was put forward by integrating multi-attribute decision and trend prediction. By analyzing the requirements'dynamic characteristics such as fuzzy, individualized and changing phase, an integrated model for the analysis and prediction of dynamic requirements based on grey system theory was constructed in which data acquisition, multi-attribute decision and trend prediction were regarded as the basic modules. Basic data gathering was completed by taking customer and market competitive factors as the data sources. Then, the importance of customer and technical requirements were analyzed by the grey corelation analysis and their recent trend knowledge were obtained with the GM(1,1) model to achieve the acquisition, analysis and prediction of requirement information in QFD. Finally, feasibility and effectiveness of the proposed method were proved by the requirements analysis of large scale air separation system.

Key words: quality function deployment, grey system theory, grey relational analysis, trend prediction, multi-attribute decision making

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