As sustainability and climate action becomes a growing priority in manufacturing, the accurate assessment of environmental impacts across the entire production chain becomes essential. Among directed energy deposition technologies, the wire and arc additive manufacturing (WAAM), offers the advantage of producing large components at high deposition rates with relatively low material and energy consumption. Recent studies have compared the environmental impacts of WAAM and conventional manufacturing methods using the life cycle assessment (LCA) approach. However, these studies have shown that the environmental benefits of WAAM are not systematic. Therefore, it appears that missing inventory flows and limited reliability of process-specific data are notable limitations to conduct these necessary studies. Thus, this research aims to address that gap by developing a methodology to supply the most accurate and reliable data to carry out an LCA of the WAAM process, thanks to an instrumented manufacturing cell. This paper presents the initial steps of this methodology, including an exhaustive inventory analysis, using a unit process tree approach. Additionally, a pedigree matrix is applied to classify the uncertainty and reliability of existing LCA database inputs. Based on these results, an instrumented WAAM cell will be designed, to collect accurate input/output data, enabling a more reliable LCA of the WAAM process. Ultimately, the outcomes of this work aim to support sustainable development of WAAM within industry. This study calls for the application of the proposed methodology to other metal additive manufacturing (MAM) processes.

Keywords: Life Cycle Assessment (LCA); Wire Arc Additive Manufacturing (WAAM); Unit Process Tree; Weidama Analysis; Pedigree Matrix