Applying data mining and grey QFD to mine the dynamic trends for computer life cycle-oriented green supply

Green products can reduce the environmental burden during design and disposal. The most approved technique to evaluate the environmental profile of a green product is the life cycle assessment. Data mining has also been successfully applied in many fields. However, little research has been done in the quality function deployment of mining the dynamic trends of customer requirements and engineering characteristics, using data mining and grey theory. This study proposed an approach to use data mining and grey theory in quality unction deployment for mining dynamic trends of the computer life cycle-oriented green supply. An Empirical example is provided to demonstrate the applicability of the proposed approach. Certain advantages may be observed when the dynamic and future requirements trends were identified, using the proposed approach. Since CRs can change rapidly, the database of CRs must be updated continually; therefore, the proposed approach in this study, will continually mine the database and identify the dynamic trends for the designers and manufacturers. The results of this study can provide an effective procedure of mining the dynamic trends of CRs and ECs for improving customer satisfaction and green competitiveness in the marketplace.

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