Enabling Environmentally-Informed Materials Selection Decisions: Robustness of Early Stage Lifecycle Assessment

Abstract

This paper explores the robustness of materials selection decisions when using various life-cycle assessment methods. Improving the environmental performance of vehicles is a topic of growing concern met by today’s designer. One approach to this goal is through vehicle mass reduction, enabled through the implementation of a growing array of material candidates. While LCA methods are available to provide quantitative input into this selection decision, LCA applications are evolving and distinct. Specifically, this paper surveys the major analytical variations of LCA implementations and explores the implications of one major variant when applied to an automotive materials selection case study involving aluminum. This case study examines analytical variations in treatment of recycling by exploring allocation methods that affect product EOL. Preliminary results indicate that the choice of analytical method can have real impacts on individual metrics and there are sets of analytical variation over which strategic results are strongly affected.