使用基于案例推理的产品生态设计的近似生命周期评估

Myeon-Gyu Jeong, J. R. Morrison, H. Suh
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引用次数: 6

摘要

由于客户环保意识的提高和严格的环保法规的出台,大多数制造企业都应在产品的整个生命周期内进行环境影响评价。生命周期评价(LCA)是一种分析产品环境负荷和评价潜在环境影响的系统方法。它可以用于生态设计和处理环境法规。然而,LCA过程通常需要大量的时间和金钱来收集相关的生命周期清单(LCI)数据和信息。通常,企业通过修改或重用类似的先前产品来开发新产品。每当他们开发新产品时,重复LCI数据收集是非常麻烦的,并且会增加交货时间。然而,如果我们基于先前的设计来估计生态影响值,那么与LCI数据收集及其参与的复杂计算程序相关的努力就会减少。尽管在流线型LCA上已经做出了各种努力来克服这些限制,但结果仍然不适合实际的生态设计。因此,我们提出了一种基于案例推理(CBR)的近似LCA方法,用于产品开发过程中快速方便的环境评价。对于近似的LCA,我们开发了功能行为结构环境效应(FBSE)表示和基于FBSE的创造性相似性度量,以实现清晰一致的CBR过程。提出了一种基于几何属性的生态影响线性建模算法,以取代复杂的LCA过程,并利用遗传算法寻找满足所提模型的最优解。以某汽车空气净化器风扇上游工艺为例,验证了基于CBR的LCA方法可有效应用于生态产品设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximate life cycle assessment using case-based reasoning for the eco design of products
Most manufacturing enterprise should perform environmental impact assessment throughout the entire life cycle of their products due to the increased environmental consciousness of customers and the introduction of strict environmental regulations. Life cycle assessment (LCA) is a systematic method of analyzing the environmental load of a product and evaluating potential environmental effects. It can be useful for eco design and for dealing with environmental regulations. However, the LCA process generally requires considerable time and money to collect relevant life cycle inventory (LCI) data and information. Usually, enterprises develop a new product by revising or reusing a similar previous product. Repeating the LCI data collection whenever they develop a new product is very cumbersome and will increase lead time. However if we estimate the eco impact values based on the previous design, then the efforts related to LCI data collection and its attending complex computational procedures are reduced. Although various efforts have been made on the streamlined LCA in an effort to overcome these limitations, the result is still unsuitable for practical eco design. We therefore propose an approximate LCA method using case-based reasoning (CBR) for a rapid and convenient environmental evaluation in product development. For the approximate LCA, we developed function behavior structure environmental effect (FBSE) representations and a creative similarity measurement based on FBSE for a clear and consistent CBR process. A geometry attribute based linear modeling algorithm of eco impact is proposed to replace complicated LCA procedures, and genetic algorithms are used to search for optimal solutions to satisfy the proposed model. A case study involving an upstream process of a vehicle air purifier fan confirms that the proposed CBR for LCA method can be effectively applied to eco product design.
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