Using grey theory in inverse QFD to analyse product reuse satisfaction for reverse logistics

  • Authors:

  • Tzu-Yuan Lee;Chih-Hung Hsu;Cheng-Yueh Tsai

  • Affiliations:

  • Department of Industrial Engineering and Management, HsiuPing Institute of Technology, Taiwan, R.O.C;Department of Industrial Engineering and Management, HsiuPing Institute of Technology, Taiwan, R.O.C;Department of Marketing and Logistics Management, Far East University, Taiwan, R.O.C

  • Venue:
  • AIC'10/BEBI'10 Proceedings of the 10th WSEAS international conference on applied informatics and communications, and 3rd WSEAS international conference on Biomedical electronics and biomedical informatics
  • Year:
  • 2010

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Abstract

In this paper, we proposed a framework of using grey theory in inverse process of QFD (quality function deployment) to analyse product reuse satisfaction based upon customer data for reverse logistics. The product reuse satisfaction of customer is a critical issue for reverse logistics, because the level of product reuse satisfaction is a key evaluation index for determining the value of reuse. On the other hand, grey theory from large database has been successfully applied in a number of advanced fields. However, little study has been done in the inverse QFD of identifying product reuse satisfaction by using grey theory. This study attempts to identify product reuse satisfaction from customer questionnaire database using a grey theory cycle for inverse QFD. We first defined the problem and constructed a customer questionnaire dataset. Second, prepared and analyzed data. Third, we used the grey theory cycle to predict the weights and determine the customer satisfaction level for inverse QFD. The results of this study can provide an effective procedure of identifying the level of product reuse satisfaction and enhance reverse logistics management in both business and customers.