Green product design is a proactive approach to minimize the product's environmental impact in green supply chain. Environmental concern about the green product gradually becomes driving force in business activity. Though the effect of this concern on the market is still invisible, the potential is continuously growing so that an environmentally friendly green product takes a higher position on the market. This study proposed a hybrid mining and predicting system to use quadratic exponential smoothing model and grey relational analysis in quality function deployment (QFD) for mining and predicting dynamic trends for life cycle assessment-oriented green supply chain. By applying the proposed system, the dynamic trends of customer requirements and technical requirements of green product can be found from a large database to enhance green competitiveness. Owing to an empirical example is provided to demonstrate the applicability of the proposed approach, the proposed system to mine and predict dynamic trends is advantageous because it can (1) find the future trends of customer requirements and technical requirements; (2) allocate limited company resources in advance; (3) provide the designers and manufacturers with well reference points to satisfy customer requirements in advance. The results of this study can provide an effective and systematic procedure of mining and predicting the dynamic trends of customer requirements and technical requirements for life cycle assessment-oriented green supply chain.
關聯:
Exponential Smoothing Model and Grey Relational Analysis
