Determination of target values of engineering characteristics in QFD using a fuzzy chance-constrained modelling approach

• Fuzzy chance-constrained modelling is used for targets setting of ECs in QFD for the first time.
• A model with minimization of fuzzy expected cost and chance constraint of satisfaction is built.
• Importance of EC is aggregation of relationships between CRs and ECs, and correlations among ECs.
• A hybrid intelligent algorithm is designed to obtain optimal decisions of the proposed model.

Quality function deployment (QFD) is a method used for the manufacturing process of a product or service that is devoted to transforming customer requirements (CRs) into appropriate engineering characteristics (ECs) by specifying the importance of the ECs and then setting their target values. Confronting the inherent vagueness or impreciseness in the QFD process, we embed the fuzzy set theory into QFD. A fuzzy chance-constrained modelling approach with core philosophies of fuzzy expected value model and fuzzy chance-constrained programming is used in this paper. Thus, a novel fuzzy chance-constrained programming model whose objective is to minimize the fuzzy expected cost is proposed to determine the target values of the ECs with risk control to ensure satisfying CRs. Meanwhile, when considering the importance of the ECs, we adopt a more reasonable dispose which is to aggregate the relationships between the CRs and the ECs, and the correlations among the ECs. In order to solve the presented model, a hybrid intelligent algorithm is designed by integrating fuzzy simulation and genetic algorithm. Finally, an example of a motor car design is given to demonstrate the feasibility and effectiveness of the devised modelling approach and algorithm.