A framework for stepwise life cycle assessment during product design with case-based reasoning

Author(s):  
Myeon-Gyu Jeong ◽  
Hyo-Won Suh ◽  
James R Morrison
Author(s):  
Awanis Romli ◽  
Rossitza Setchi ◽  
Paul Prickett ◽  
Miguel P de la Pisa

Several methods and tools have been developed to facilitate sustainable product design, but they lack critical application of the ecological design (eco-design) process and economic costing, particularly during the conceptual design phase. This research study overcomes these deficiencies by integrating eco-design approaches across all phases of the product life cycle. It proposes an eco-design case-based reasoning tool that is integrated with the recently developed ecological quality function deployment method, which supports sustainable product design. The eco-design case-based reasoning tool is an intuitive decision-support tool that complements the ecological quality function deployment method and proposes solutions related to customers’ requirements and the environmental and economic impacts of the product. The ecological quality function deployment method ensures that customers’ needs are considered within the context of product sustainability. The novelty of this article is in the development of the eco-design case-based reasoning tool which is based on the premise that if experiences from the ecological quality function deployment process can be captured in some useful form, designers can refer to and learn from them. This approach helps industrial decision-makers propose solutions by reusing solutions from similar cases and from their past experiences. The novelty is in the way the cases are structured and new cases are generated, using life-cycle assessments, cost estimations, and information about related manufacturing processes and means of transportation. This article demonstrates the applicability of the proposed approach through an industrial case study.


Author(s):  
Shuyi Wang ◽  
Daizhong Su ◽  
You Wu ◽  
Zijian Chai

Abstract An approach for integrating life-cycle assessment (LCA) into the eco-design of lighting products was developed, and LCAs of five lighting products that are currently on the market were then carried out using this approach. Based on the results of these LCAs, the sustainability requests for lighting products were derived and embedded into the product design specification (PDS), thus ensuring that any product developed according to the PDS would have the desired eco-design features. A new sustainable lighting product was then designed according to the PDS and manufactured, after which the new product underwent LCA. Upon comparing the results of the LCA of the new product with the LCA results for the existing lighting products, the newly designed product was found to provide better environmental performance than the existing products (a 27–58% reduction in environmental impact).


2014 ◽  
Vol 12 (3) ◽  
pp. 307-315 ◽  
Author(s):  
Sekar Vinodh ◽  
Gopinath Rathod

Purpose – The purpose of this paper is to present an integrated technical and economic model to evaluate the reusability of products or components. Design/methodology/approach – Life cycle assessment (LCA) methodology is applied to obtain the product’s environmental performance. Monte Carlo simulation is utilized for enabling sustainable product design. Findings – The results show that the model is capable of assessing the potential reusability of used products, while the usage of simulation significantly increases the effectiveness of the model in addressing uncertainties. Research limitations/implications – The case study has been conducted in a single manufacturing organization. The implications derived from the study are found to be practical and useful to the organization. Practical implications – The paper reports a case study carried out for an Indian rotary switches manufacturing organization. Hence, the model is practically feasible. Originality/value – The article presents a study that investigates LCA and simulation as enablers of sustainable product design. Hence, the contributions of this article are original and valuable.


Author(s):  
Julie L. Eisenhard ◽  
David R. Wallace ◽  
Ines Sousa ◽  
Mieke S. De Schepper ◽  
Jeroen P. Rombouts

Abstract Prior work has demonstrated the integration of detailed life-cycle assessment into a traditional design modeling process. While a full life-cycle assessment provides insight into a product’s potential impact on the environment, it is often too time consuming for analysis during conceptual product design, where ideas are numerous and information is scarce. The work presented in this paper explores an approximate method for preliminary life-cycle assessments without detailed modeling requirements. Learning algorithms trained on the known characteristics of existing products allow the environmental impacts of new products to be approximated quickly during conceptual design. Artificial neural networks train on product attributes and environmental impact data from pre-existing life-cycle assessment studies. The product design team queries the trained artificial model with new high-level product attribute data to quickly obtain an approximate impact assessment for a new product concept. Tests based on simplified inventory data have shown it is possible to predict impacts on life-cycle energy consumption, and that there is a basis for the method to be used in also predicting solid material, greenhouse effect, ozone layer depletion, acidification, eutrophication, winter smog, and summer smog.


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