Quality function deployment (QFD) is a planning and problem-solving tool for translating customer requirements (CRs) into the engineering characteristics (ECs) of a product. Owing to the typical vagueness of functional relationships in a new product, product planning is becoming more difficult under uncertainties. To tackle the vagueness or imprecision in QFD, numerous scholars have applied the fuzzy set theory to QFD and proposed various fuzzy QFD models. In this study, a fuzzy linear programming model is developed to determine the optimal level of ECs, where the objective function is the overall customer satisfaction and the cost constraint is fuzzified. Finally, we use a software product design as a numerical example, which demonstrates that the proposed methodology can help the QFD team realize the overall customer satisfaction of new products catching up with or exceeding the competitors in the target market. 1. Introduction Being able to perform new product development in a short lead time and at a low cost is the key to improve competitiveness for enterprises in the global market. To successfully fulfill it, the key is to apply customer-driven design and manufacturing approach in enterprises. Customer requirements (CRs) play a vital role in the design of products and services. Originated in Japan in the late 1960s [1], quality function deployment (QFD) is a planning and problem-solving tool for translating CRs into the engineering characteristics (ECs) of a new product. QFD is a structured approach to defining customer requirements and translating them into specific plans to develop products or services to meet those CRs. QFD has been widely known to be one of the most useful tools in customer-driven products or services development [1–4]. As far as product planning and development decisions are concerned extensively, the application of QFD has been applied in many areas [1–3]. QFD can help the design team systematically determine ECs for developing a new product with maximum customer satisfaction. The core concept of QFD is to translate CRs to ECs and subsequently into part characteristics, process parameters, and production requirements. Accordingly, the QFD process includes four sets of matrices called houses of quality (HOQ) to relate CRs to product planning, parts deployment, process planning, and manufacturing operations [1]. The determination of the ECs’ target levels has attracted increasingly more and more researchers’ attention recently. The process of setting the target levels of ECs is accomplished in a subjective adc manner or in a
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