衍生性電子產品生命週期之環境衝擊與績效評估方法論

Methodology for Environmental Impact and Performance Assessment of Product Life Cycle of Derivative Electronic Products

王同德(Tung-Te Wang)

指導教授 ： 車振華

國立臺北科技大學/管理學院/工業工程與管理研究所/碩士(2010年)

摘要

近年來生態環境破壞的問題日益嚴重，且自然資源快速耗竭，使得環保意識迅速高漲。有鑑於此，企業必須降低整個產品生命週期對生態環境所造成的衝擊。為協助企業面對上述之挑戰，因此，本研究運用倒傳遞類神經網路建立衍生性電子產品生命週期之有害化學物質與能源消耗分析模式，協助企業在產品設計階段估計衍生性電子產品在生命週期各主要階段對環境所造成的危害。此外，為了解新產品之生態化設計之績效，因此，本論文運用偏好順序評估法（Technique for Order Preference by Similarity to Ideal Solution, TOPSIS）發展產品環境化設計績效評估模式。透過上述之分析，可以協助企業了解新產品與現有競爭對手之相似性產品之環境化設計績效，提供產品設計修正之參考。

關鍵字

產品生命週期 ； 產品設計 ； 倒傳遞類神經網路 ； 環境化設計

並列摘要

With increasingly serious ecological degradation and rapidly exhausted natural resources, environmental consciousness has been spreading worldwide instantly in recent years. For this reason, enterprises have to reduce impacts of the entire product life cycle on the ecological environment. To help enterprises address the foregoing challenges, this study therefore uses a back-propagation neural network (BPNN) to establish a model for analysis of hazardous chemicals and energy consumption of the product life cycle of derivative electronics, helping enterprises, at the product design stage, estimate hazards of derivative electronic products on the environment across major phases of the product life cycle. In addition, to clarify the performance of a newly developed product’s ecological design, this paper applies TOPSIS to develop a performance assessment model for product design for environment (DfE). With the analysis provided above, we may help enterprises better understand DfE performance of its new product as well as similar products of competitors as a reference for modification of product design.

並列關鍵字

Product life cycle ； Product design ； Back-propagation Neural Network (BPNN) ； Design for environment (DfE)

參考文獻

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