Prioritizing Design for Environment Strategies Using a Stochastic Analytic Hierarchy Process

Abstract

This paper describes a framework for applying design for environment (DfE) within an industry setting. Our aim is to couple implicit design knowledge such as redesign/process constraints with quantitative measures of environmental performance to enable informed decision making. We do so by integrating life cycle assessment (LCA) and multicriteria decision analysis (MCDA). Specifically, the analytic hierarchy process (AHP) is used for prioritizing various levels of DfE strategies. The AHP network is formulated so as to improve the environmental performance of a product while considering businessrelated performance. Moreover, in a realistic industry setting, the onus of decision making often rests with a group, rather than an individual decision maker (DM). While conducting independent evaluations, experts often do not perfectly agree and no individual expert can be considered representative of the ground truth. Hence, we integrate a stochastic simulation module within the MCDA for assessing the variability in preferences among DMs. This variability in judgments is used as a metric for quantifying judgment reliability. A sensitivity analysis is also incorporated to explore the dependence of decisions on specific input preferences. Finally, the paper discusses the results of applying the proposed framework in a realworld case.