【作者】 赵有；

【导师】 何桢；

【作者基本信息】 天津大学 ， 工业工程， 2007， 博士

【摘要】 随着全球化市场的形成,企业面临的是以顾客需求为驱动的全球市场,竞争焦点已经集中于如何更好地满足个性化的顾客需求。这其中的核心就是产品的规划和设计。六西格玛设计是以顾客需求驱动的、基于并行工程和DFX(Design for X)的思想、面向产品生命周期的系统设计方法论。实施六西格玛设计是企业加强竞争力的有效措施。然而,当前我国企业实施6σ设计存在的主要问题之一是:缺乏对顾客需求获取、转化、管理和分析的深入研究。针对这一问题,研究六西格玛设计中顾客需求分析关键技术是一个有重要意义的课题。本文对这一课题进行了系统的深入研究。主要内容如下:(1)阐述了企业所处的环境特征及产品设计的重要地位,同时对学术界内已有的产品设计研究相关理论进行了综述,并阐明本文研究意义。(2)对新环境下顾客需求获取方法进行了系统研究。结合数据挖掘和WEB挖掘技术的应用研究,研究了基于WEB2.0信息源的顾客需求信息获取原型。建立了基于模糊c-平均法的需求聚类方法。提出了考虑市场竞争基于粗糙集理论和信息熵方法的顾客需求重要度确定方法。(3)将来自顾客视角的、模糊的需求信息转化为设计视角的、量化的、具有工程意义的技术特性是必要的。针对QFD规划过程的内在模糊性,把证据理论和模糊数知识协同算法应用于QFD的产品规划过程。研究了技术特性配置和自相关性模糊信息的协同处理方法,进而构建了一个QFD产品规划模型。提出了顾客需求向技术特性转化的数学模型,应用基于α-截集的模糊平均加权部分非线性规划方法计算技术特性重要度,应用平均水平截集法去模糊化并对技术特性进行排序。研究了模糊约束条件下技术特征满意度最大化的需求转化线性规划模型。(4)针对设计早期质量屋信息的模糊性和不确定性。提出了一种设计方案早期评价模糊群决策模型。在评价属性为模糊数或不确定语言变量的情况下,分别应用模糊TOPSIS折衷群决策方法和基于语言变量算子群决策方法对模型进行评价决策。更多还原

【Abstract】 With the formation of world market, enterprises are faced with a customer-driven global market, the competition have focused on how to satisfy the individual customer’s requirements better. The core is product planning and design. Design for Six Sigma(DFSS) is a system design methodology which is driven by customer requirements, and based on concurrent engineering and DFX(Design for X) ideas, and faced with product life cycle. DFSS is an effective measure for enterprises to strengthen the competitiveness. However, a main problem is lack of analysis study to customer requirements acquiring, transformation and management for china enterprises to implemente DFSS. Based on this problem, study on the key technology of customer requirements analysis in DFSS is an important problem. This paper makes further systematic study on it. The main content is as follows:Firstly, this paper expounds the surrounding characters of Chinese enterprises and the important of product planning and design. In the mean time, it summarizes the interrelated theories on product planning and design in academe and then gives the research significance.Secondly, the method of acquiring customer requirements is studied systematically under the new environment in this dissertation. The actual state of research on and application of data mining and WEB mining are analyzed in detail. An prototypes of acquiring customer requirements based on WEB2.0 data source is studied. The Voice of Customers (VOC) clustering analysis model based on c-means method is built. A Rough Sets theory-based method for determining importance of customer requirements is proposed, in which the concept of entropy is introduced for customer requirements competitive analysis.Thirdly, it is essential to transform the fuzzy customer requirements into the quantitative and design-oriented engineering indices. For the inherent fuzziness in QFD model, it applies the evidence theory and fuzzy theory in QFD product planning progress and studies the methods of handing the fuzzy information collaboratively of the deployment and correlation among engineering characteristics, and puts forward the product planning model based on QFD. A model which translates the customer requirements into the technical characteristics is proposed. The importance of the technical characteristics are calculated by solving a pair of nonlinear program based onα-cuts fuzzy weighted average, and rated by the averaging level cuts method to defuzzfy A model maximizing the satisfaction of the selected technical characteristics with consideration of resource constraints is also built.Finally, according to fuzzy and uncertain of House of Quality information in the early stage of design. The paper proposes a kind of fuzzy group of decision model, in which the information on attribute is triangular fuzzy numbers or uncertain linguistic labels. The model is assessed by fuzzy TOPSIS method and based on ULHA linguistic operator fuzzy group decision making method.更多还原