Abstract
Quality function deployment (QFD) is a methodology to ensure that customer requirements (CRs) are deployed through product planning, part development, process planning and production planning. The first step to implement QFD is to identify CRs and assess their relative importance weights. This paper proposes a nonlinear programming (NLP) approach to assessing the relative importance weights of CRs, which allows customers to express their preferences on the relative importance weights of CRs in their preferred or familiar formats. The proposed NLP approach does not require any transformation of preference formats and thus can avoid information loss or information distortion. Its potential applications in assessing the relative importance weights of CRs in QFD are illustrated with a numerical example.
Acknowledgements
The work described in this paper is supported by the National Natural Science Foundation of China (NSFC) under the Grant No.70925004 and also substantially supported by a grant from City University of Hong Kong (project no.7002571). The author would like to thank two anonymous reviewers for their constructive comments, which have helped to improve the paper.