Abstract

Life cycle assessment (LCA), standardized by ISO 14040, is today's most commonly used method for analysis of environmental impact and sustainability and an aid to decision-making in the industry. However, LCA’s inherent flexibility and associated uncertainty sources are causing inconsistencies in the assessment results if different assessors with similar backgrounds analyze identical input data and use identical LCA software. The authors identified and quantified this problem at Stanford University while using LCA for environmental impact analysis of additive manufacturing (AM), popularly known as 3D printing, compared to conventional manufacturing, for the production of metallic building components. To address the identified inconsistencies, the authors formalized a semiautomated assessment framework that improved the consistency of the LCA results by a factor of four in total, but specific inconsistencies remained. The authors then conducted an uncertainty analysis to identify the uncertainty sources causing inconsistencies, quantify their impact on the LCA results, and propose mitigations. The uncertainty analysis found that the use of the formalized framework reduces the impact of the behavioral uncertainty source category, such as decision-making and preferences, and the interaction category, such as teamwork. The proposed mitigations include the development of direct automated links to design and LCA software and the development of product models of existing AM processes for LCA databases. The proposed mitigations cannot fully influence the impact of the epistemic behavioral uncertainty sources, such as the learning process. Future work includes testing the methodology and the findings with more cases and on other similar process-based LCAs.