Fuzzy Solution for Kano’s Quality Model

For designing and developing products/services it is vital to know therelevancy of the performance generated by each technical attribute and howthey can increase customer satisfaction. Improving the parameters of technicalattributes requires financial resources, and the budgets are generally limited.Thus the optimum target is to achieve maximum customer satisfaction withingiven financial limits. Kano’s quality model classifies the relationshipsbetween customer satisfaction and attribute-level performance and indicatesthat some of the attributes have a non-linear relationship to satisfaction, ratherpower-function should be used. For the customers’ subjective evaluation theserelationships are not deterministic and are uncertain. This paper proposes amethod for fuzzy extension of Kano’s model and presents numerical examplesthat can prove the efficiency of bacterial evolutionary algorithm in as well.