AutoLCA: A Framework for Sustainable Redesign and Assessment of Products
计算机科学
持续性
过程(计算)
质量(理念)
作者
M. Shahriar Hossain,Manish Marwah,Amip J. Shah,Layne T. Watson,Naren Ramakrishnan
出处
期刊:ACM Transactions on Intelligent Systems and Technology [Association for Computing Machinery] 日期:2014-04-30卷期号:5 (2): 34-被引量:5
标识
DOI:10.1145/2505270
摘要
With increasing public consciousness regarding sustainability, companies are ever more eager to introduce eco-friendly products and services. Assessing environmental footprints and designing sustainable products are challenging tasks since they require analysis of each component of a product through their life cycle. To achieve sustainable design of products, companies need to evaluate the environmental impact of their system, identify the major contributors to the footprint, and select the design alternative with the lowest environmental footprint. In this article, we formulate sustainable design as a series of clustering and classification problems, and propose a framework called AutoLCA that simplifies the effort of estimating the environmental footprint of a product bill of materials by more than an order of magnitude over current methods, which are mostly labor intensive. We apply AutoLCA to real data from a large computer manufacturer. We conduct a case study on bill of materials of four different products, perform a “hotspot” assessment analysis to identify major contributors to carbon footprint, and determine design alternatives that can reduce the carbon footprint from 1p to 36p.