Abstract
The strengthened environmental regulatory requirements and general awareness of the need for environmental conservation worldwide, design for environment has become a key design criterion in new product development processes. Due to their resources-consuming attribute and the prerequisite expert knowledge in environmental sciences for the impacts interpretations, the existing forms of product-oriented environmental impact assessment methods are impractical to be adopted by product designers in small-and-medium enterprises. Life Cycle Assessment (LCA) is a generally accepted quantitative approach to assess a product’s environmental impact. However, a full LCA study often requires a considerable amount of data and therefore, it is regarded as not a handy tool for product design evaluations particularly at the initial design stage. This leads to our intention to develop an immediately applicable approach for decision-makers to evaluate the design options. The proposed approach integrates Analytic Hierarchy Process and Fuzzy Theory, with Evidential Reasoning (ER) to support the environmental impact evaluations of design options. A case study is carried out to demonstrate its applicability to prioritize the environmental impact of various design options. A symmetrical triangular distribution is introduced for calculating the expected utility and for testing the sensitivity of results.
| Original language | English |
|---|---|
| Pages (from-to) | 141-151 |
| Number of pages | 11 |
| Journal | International Journal of Sustainable Engineering |
| Volume | 9 |
| Issue number | 2 |
| Early online date | 2 Feb 2016 |
| DOIs | |
| Publication status | Published - 3 Mar 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 8 Decent Work and Economic Growth
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 12 Responsible Consumption and Production
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SDG 13 Climate Action
User-Defined Keywords
- eco design
- evidential reasoning
- fuzzy
- Life cycle assessment
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