Integrating process replicability in the life cycle assessment of manufacturing fiber-reinforced polymer composites

The manufacturing process influences component quality and environmental performance of products such as fiber-reinforced polymer composites. Previous Life Cycle Assessments (LCA) consider process functionality and related environmental aspects only to a limited extent, often due to insufficient application of existing guidelines. To address this limitation, this study compares a manual and an automated composite manufacturing process under two sets of process parameters. A particular focus is placed on integrating process replicability into functional unit and life cycle inventory through the usage of standardized statistical indices to derive defect rates. The functional unit of the attributional LCA is defined as the manufacturing of one bio-based composite plate that meets quality requirements defined by process performance indices based on flexural modulus. To focus on manufacturing, gate-to-gate system boundaries are selected and product materials are considered only regarding defect production and processing scraps. While process replicability influences the magnitude of the case study results, shorter process duration under higher temperatures lead generally to lower environmental impacts for both types of manufacturing processes. The competitive performance of automated or manual process depends on impact category and exhibits sensitivity to product mass and defect rate. Different options to model other inventory groups, such as filling data gaps for consumables, measured, calculated and literature-based options for energy quantification, infrastructure modelling, and tangible inputs of human labor, exhibit varying influence on LCA results. Despite limitations of the case-study approach, this work demonstrated feasibility and discussed the relevance of including process replicability into LCA. Future research should investigate integrability and relevance under other technical and methodological framework conditions.