Study On The Key Techniques Of Customer Requirement Analysis In Design For Six Sigma

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.