Abstract

Quality function deployment (QFD) is a proven tool for process and product development, which translates the voice of customer (VoC) into engineering characteristics (EC), and prioritises the ECs, based on the customer's requirements. Conventional QFD evaluates these targets for crisp weights of the customer attributes (CA), identified from the VoCs. The VoCs are not crisp and generally exhibit a well‐defined distribution. Crisp weights assigned to non‐crisp CAs can lead to wrong prioritisation of the EC. In the past, fuzzy numbers have been used to represent the imprecise nature of these judgements and to define more appropriately the relationship between EC and CA. This paper proposes fuzzy logic‐quality function deployment (FL‐QFD) – the use of fuzzy logic principles in QFD. It is an innovative method of determining optimum rating of ECs by simulating the QFD matrix for randomized CA rating in the fuzzied range. The rule‐based knowledge system defines the relationship between the ECs and the CAs. The flexible manufacturing system (FMS) design problem investigated by Khoo and Ho (Khoo, L.P. and Ho., N.C., “Framework of a fuzzy quality function deployment system”, International Journal of Production Research, Vol. 34, 1996, pp. 299‐311) is presented to show the application of the proposed model. The results are compared and examined to study the effect of the CA on prioritising the EC. The paper addresses the issue of defining non‐crisp customer attributes in the QFD, and offers practical help to an individual intending to further investigate the proposed model.

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