Research On Quality Function Deployment Based On Uncertain Multiple Attribute Decision Making

Quality function deployment is a systematic, structured method for product development and quality management to realize customer requirements throughout the whole process of its application in the form of sequential decision. The decision information is centralized and the decision process is transparent. With the normalization of its important processes, the method can be self-documenting. Currently, product market competition continues to accelerate, the diversification and personalization of customer requirements has already become the trend, product/service development is becoming increasingly complex, thus quality function deployment has a good practical significance and application prospects.The process of quality function deployment is the processing flows of information. From the original customer requirements, all the relevant information is collected and handed to refine the required design knowledge to support the subsequent decisions. The vagueness and complexity of knowledge, the diversity and uncertainty of the information form, and the special needs of knowledge for decision making hinder the implementation of quality function deployment. The Uncertain Multiple Attribute Decision Making methods are technical decision aids for evaluating alternatives characterized by multiple attributes under uncertain environment, which has intrinsically close contact with many problems of quality function deployment. This research combines the Uncertain Multiple Attribute Decision Making methods to explore some key issues in quality function deployment. We hope our research can help this effective method better adapt to the uncertainty enviroment, enrich and improve the quality function deployment methodology, and provide technical support for the development of product/service in manufacturing firms. The major achievements and innovations of this dissertation are summarized as follows:1) To deal with the the vagueness and incompleteness of customer preference in customer requirements analysis, a method on the basis of incomplete linguistic judgment matrices to analysis the importance of customer requirements is proposed. Each individual preference is represented by an additive linguistic judgment matrice and extended to a complete form when certain elements are missing. Then all these extended matrices are aggregated into a collective one in order to obtain the importance of customers’requirements. The method can not only solve the problem of information missing in customer surveys, but also reduce the burden of the evaluators, and help them to focus on their own concerns, thus improves the result accuracy.2) To deal with the diversity and uncertainty of information in customer requirements analysis, a method integrating market competitive information in product planning house of quality and Kano model to adjust the fundamental importance ratings of customer requirements is given. In order to min knowledge from the competitive information, the concepts of the competitive priority ratings and the improvement ratios of customer requirements are proposed, which reflect the need for competition from the customers perspective and the firm’s willingness to improve its product performance, respectively. Their solving formulas are also derived. Two-factor analysis is utilized to identify the different categories of customer requirements and estimate the Kano regulators. By using the competitive priority ratings, the improvement ratios and the Kano regulators to correct the fundamental importance ratings, the final importance ratings of customer requirements are determined. It makes designers pay more attention to customer requirements that have larger potential contribution in enhancing the competitiveness and improving customer satisfaction.3) According to the characteristics of information source types in translation from customer requirements to technical characteristics by using house of quality, a synthetic method utilizing the subjective and objective information in house of quality to determine the priority ratings of technical characteristics is proposed. In subjective weighting, decision-makers can choose linguistic terms to evaluate the relationship between customer requirements and technical characteristics according to their own preference. The weighted averaging operator and the linguistic hybrid operator are used to aggregate the individual judgments into a collective value for each technical characteristic, reflecting the importance degrees of both the given argument and its ordered position. In objective weighting, uncertain values of technical characteristics are given in the form of internal numbers. Based on technical competitive information, a goal-deviation matrix is conducted in order to obtain objective importance ratings by using entropy methods. The final result is weighted value of the subjective and objective calculation, which coordinates and unifies the wisdom of experts and the data-based reasoning.4) According to the characteristics of the goal and criteria in decision making for product design alternatives, an evaluation model combining analytic hierarchy process with preference ranking organization method for enrichment evaluations is proposed. Based on the combination of quantitative and qualitative decision criteria system, analytic hierarchy process is used to determine the weight for criteria. Preference ranking organization method for enrichment evaluations is used to calculate the net flow to obtain the ranking of the design alternatives. This approach takes into account the uncertainty of the attribute information and orients to the designer’s goals and values, thus has certain implication in product design.5) Due to the fact that quality function deployment and service operations coincide in their core ideas, a product service deployment methodology based on quality function deployment is proposed. On the basis of analyzing product service from the perspective of the general concept and content of service, quality function deployment tools are utilized to transform customer requirements for product service into the specific objectives of each stage. The process of quality function deployment for product service is designed and a group decision method to determine the importance ratings of service attributes is given, that can creat a new way for product service deployment.Finally, a series of real-world product/service development cases prove the feasibility and effectiveness of the abovementioned methods in this paper.