A Parametric Life Cycle Modeling Framework for Identifying Research Development Priorities of Emerging Technologies: A Case Study of Additive Manufacturing

Life Cycle Assessment (LCA) has been used to assess the environmental implications of emerging technologies in different manufacturing sectors. However, it is challenging to use the traditional LCA method to model the relationships between Life Cycle Inventory (LCI) data and key technical parameters, preventing further analysis for understanding key driving factors and determining priorities for research and technology development. Furthermore, the sensitivity analysis of traditional LCA could be misleading for decision making or strategic planning given that the potential/possibility of improving specific parameters are commonly not taken into consideration. In this work, a novel parametric analysis framework was developed to address the methodological challenge. The modeling framework integrates process-based engineering models with LCA, Life Cycle Cost analysis (LCC), and optimization. The framework is demonstrated through a case study of additive manufacturing (AM). (C) 2019 The Authors. Published by Elsevier B.V.