Value Of Information Analysis For Life Cycle Assessment: Uncertain Emissions In The Green Manufacturing Of Electronic Tablets

JOURNAL OF CLEANER PRODUCTION(2018)

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Abstract
Optimization of manufacturing processes and practices requires multiple tradeoffs among often competing priorities. This is especially the case for green manufacturing, where meeting sustainability goals often requires the use of more expensive materials and technologies with uncertain effects on product performance. Not only are decisions regarding such trade-offs difficult to make, these decisions often need to be made with incomplete and uncertain information. These scenarios often result in requests for more information, some of which may be irrelevant for the decision at hand. Value of information (Vol), a decision analytic method for quantifying the expected benefit of acquiring additional information, can be used to improve a wide range of manufacturing decisions. By identifying the contribution of specific model parameter uncertainty to total product or decision uncertainty, Vol can prioritize additional data collection and research strategies to optimally reduce uncertainty and support decisions, i.e., identifying the greatest "bang for the buck." Vol has been used in many fields including medicine, ecology, and economics, but is rarely used in manufacturing and has never been applied within life cycle assessment (LCA), e.g., to address uncertainty in product development decisions. This paper discusses the use of Vol with LCA in manufacturing and details a case study in which we calculate Vol related to the lifecycle environmental impact of electronic tablet production. We found that LCA-Vol can be successfully used to triage the data gathering process in electronic tablets, to more accurately describe lifecycle environmental impact. We anticipate future applications of LCA-Vol to lead to more cost-effective and sustainable production. Published by Elsevier Ltd.
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Key words
Value of information analysis, Life cycle assessment, Green manufacturing, Decision analysis
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