A hybrid methodology of fuzzy grey relation for determining multi attribute customer preferences of edible oil
The main idea behind this study is to introduce a fuzzy grey relational methodology (FGRM) to determine the importance of customer attributes (CAs) for edible oil, particularly for defining the opportunity of competitiveness which has recently become one of an important concern of manufacturing companies. It was also aimed to seek high quality level of product and process characteristics for meeting the desirability of attributes and for health care. A fuzzy grey inference system was employed with the support of fuzzy quality function (QFD) deployment to interpret the qualitative and imprecise customer attributes. Fuzzy QFD is relatively a recent methodology offering a more in-depth analysis and investigation into the handling of customer requirements and engineering characteristics. The attributes then were defuzzified into quantitative values by amalgamating the knowledge of the customers and the product designers. Customer needs (CNs) are the voice of customers and tend to be linguistic naturally. In this study, fuzzy inference system (FIS) along with fuzzy QFD was employed to determine the desirability of edible oil by consumers. Fuzzy QFD is a powerful tool for improving product design and quality, and procuring a customer-driven quality system. The integrated framework based on FIS, fuzzy QFD and FGRM determined the CAs relations, and desirability level of edible oil by consumers. The findings are not only meaningful for customers, but also important for market position of product. The methodology significantly reduces the complexity of decision making and increase the production efficiency and overall competitiveness.
fgrm fuzzy qfd customer needs fuzzy inference system ecs