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The implementation of quality function deployment based on ...

The implementation of quality function deployment based on ...

The implementation of quality function deployment based on

Journal ong>ofong> Intelligent Manufacturing 12, 65±75, 2001 # 2001 Kluwer Academic Publishers. Manufactured in ong>Theong> Netherlands. ong>Theong> ong>implementationong> ong>ofong> ong>qualityong> ong>functionong> ong>deploymentong> ong>basedong> on linguistic data X. X. SHEN, K. C. TAN and M. XIE Department ong>ofong> Industrial and Systems Engineering, National University ong>ofong> Singapore Received March 1999 and accepted March 2000 Quality ong>functionong> ong>deploymentong> (QFD) is a customer-driven ong>qualityong> management and product development system for achieving higher customer satisfaction. ong>Theong> QFD process involves various inputs in the form ong>ofong> linguistic data, e.g., human perception, judgment, and evaluation on importance or relationship strength. Such data are usually ambiguous and uncertain. An aim ong>ofong> this paper is to examine the ong>implementationong> ong>ofong> QFD under a fuzzy environment and to develop corresponding procedures to deal with the fuzzy data. It presented a process model using linguistic variables, fuzzy arithmetic, and defuzzi®cation techniques. Based on an example, this paper further examined the sensitivity ong>ofong> the ranking ong>ofong> technical characteristics to the defuzzi®cation strategy and the degree ong>ofong> fuzziness ong>ofong> fuzzy numbers. Results indicated that selection ong>ofong> the defuzzi®cation strategy and membership ong>functionong> are important. This proposed fuzzy approach allows QFD users to avoid subjective and arbitrary quanti®cation ong>ofong> linguistic data. ong>Theong> paper also presents a scheme to represent and interprete the results. Keywords: Quality ong>functionong> ong>deploymentong>, house ong>ofong> ong>qualityong>, fuzzy set theory, linguistic variable, fuzzy number, sensitivity analysis 1. Introduction Quality is viewed as an essential means ong>ofong> competing in today's rapidly changing global marketplace. Total ong>qualityong> management (TQM), a philosophy or approach to management, has emerged as an important aspect ong>ofong> overall ong>qualityong> improvement programs in many organizations. It is both a comprehensive managerial philosophy as well as a collection ong>ofong> tools and approaches for its ong>implementationong> (Evans and Lindsay, 1996). Focusing on listening to the voice ong>ofong> the customer (VOC), ong>qualityong> ong>functionong> ong>deploymentong> (QFD) is an essential tool for implementing TQM (Guinta and Praizler, 1993). QFD deploys the voice ong>ofong> the customer throughout the R&D, engineering, and manufacturing stages ong>ofong> product development (Grif®n and Hauser, 1993). It is a powerful system for ong>qualityong> improvement and product development which assures that ong>qualityong> is built into new products and services. Various techniques have been identi®ed and studied with an aim to improving the QFD methodology. One emerging trend involves the use ong>ofong> arti®cial intelligence (AI) and related techniques. For example, Reich (1996) discussed the bene®ts that AI can bring to QFD. To avoid the need to input a large amount ong>ofong> data and the necessity ong>ofong> estimating values on a rather subjective basis, Zhang et al. (1996) suggested a machine learning approach. However, the QFD process involves various inputs in the form ong>ofong> linguistic data, e.g., human perception, judgment, and evaluation on importance ong>ofong> customer requirements or relationship strength, which are usually subjective and uncertain. In traditional QFD most ong>ofong> these input variables are assumed to be precise and are treated as numerical data. Linguistic data, however, is inherently vague and ambiguity. ong>Theong>y can be treated to approximate exactness with the help ong>ofong> fuzzy set theory. Some progress has been made along this line. Masud and Dean (1993) investigated how QFD analysis can be performed when input variables are

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