Dealing With Dissatisfaction Measure In QFD Model To Derive Target Of Engineering Characteristics
DOI:
https://doi.org/10.23055/ijietap.2011.18.12.295Keywords:
Consumer Product DesignAbstract
Abstract. Quality Function Deployment (QFD) is a design tool for developing product to maximize customer satisfaction. Implementation of QFD demands deeply understanding about customer requirements. Kano model is broadly used to give insight about customer requirements categories. In the Kano model there are three major categories that have to be considered regarding its influence on customer’s satisfaction or dissatisfaction. Attractive requirements and must be requirements have more than proportional influence on customer’s satisfaction or dissatisfaction. One dimensional requirements are requirements that affect customer satisfaction proportionally. In dealing with factors that lead to satisfaction or dissatisfaction, Kano model is considered parallel to Motivation-Hygiene (M-H) theory. According to Kano model and M-H theory, fulfilling factors that lead to satisfaction is not automatically eliminating dissatisfaction. In Kano model, factors that merely lead to satisfaction (attractive requirements) differ from those that only lead to dissatisfaction (must be requirements). A number of studies on QFD have tried to incorporate Kano model into QFD process. Some of those which proposed mathematical model used nonlinear function to represent requirements that have disproportional influence on satisfaction. However, those studies focused mainly in maximizing customer satisfaction without paying much attention in dissatisfaction measurement. This research is conducted to deal with maximizing customer satisfaction and minimizing dissatisfaction as well. A mathematical model is developed to set target of engineering characteristics. Verification of model developed is done by a simple hypothetical case. Although it shows that it is well verified, validation is still needed. It may be done in the future by implementing the model for solving real cases.
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