A combined fuzzy linear regression and fuzzy multiple objective programming approach for setting target levels in quality function deployment

• Published in: Expert systems with applications Vol. 38; no. 4; pp. 3015 - 3022
• Main Authors: Sener, Zeynep, Karsak, E. Ertugrul
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2011
• Subjects: Budgeting; Customer satisfaction; Fuzzy; Fuzzy linear regression; Fuzzy logic; Fuzzy multiple objective programming; Fuzzy set theory; House of quality; Maximization; Multiple objective; Quality function deployment; Regression; Quality function deployment; Fuzzy linear regression; Fuzzy multiple objective programming; House of quality
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2010.08.091

► Target levels are obtained by using fuzzy regression and multi-objective programming. ► Fuzzy regression identifies the relationships between CNs and ECs, and among ECs. ► Both customer satisfaction and enterprise satisfaction are considered. ► Customer satisfaction is considered with design objectives subject to a budget constraint. Quality function deployment (QFD) is a systematic process for translating customer needs into engineering characteristics, and then communicating them throughout the enterprise in a way to ensure that details are quantified and controlled. The inherent fuzziness of relationships in QFD modeling justifies the use of fuzzy regression for estimating the relationships between both customer needs and engineering characteristics, and among engineering characteristics. Albeit QFD aims to maximize customer satisfaction, requirements related to enterprise satisfaction such as cost budget, extendibility, and technical difficulty also need to be considered. This paper presents a fuzzy multiple objective decision framework that includes not only fulfillment of engineering characteristics to maximize customer satisfaction, but also maximization of extendibility and minimization of technical difficulty of engineering characteristics as objectives subject to a financial budget constraint to determine target levels of engineering characteristics in product design. A real-world quality improvement problem is presented to illustrate the application of the decision approach.