A design for environment methodology for evaluation and improvement of derivative consumer electronic product development

Abstract

Increasing environmental awareness and stringent environmental regulations have motivated many companies to incorporate ecodesign into product development. To assist companies to address the challenge, this research presents a design for environment (DfE) methodology to evaluate and improve derivative consumer electronic product development using a back-propagation neural network (BPNN) model and a technique for order preference by similarity to ideal solution (TOPSIS) method. Based on use of a BPNN, the life cycle assessment (LCA) models are developed to estimate quantities of hazardous chemical substances and energy consumption for a derivative consumer electronic product throughout the product life cycle. A performance evaluation and improvement model for DfE is then devised based on the TOPSIS method to analyze the ecodesign performance and provide concrete improvement strategies. With the aforementioned analysis of environmental performance, an enterprise can profoundly understand and significantly enhance the relative DfE performance of a new product compared to the similar competitive products. Finally, we apply an optical mouse development project as a case to elaborate and demonstrate the effectiveness of the proposed methodology. These analytical results can let us understand the DfE performance ranking and acquire the maximum reduced quantity of each DfE criterion for each module of a new product. Meanwhile, to enhance the green competitiveness of the new product, we recommend that the engineers should decrease the area of the circuit board of the new product. In addition, the material of the USB cable for the new product should be switched from the PVC material to the PE material.

Keywords

Back-propagation neural network / TOPSIS / design for environment / ecodesign / product development

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