Life Cycle Assessment (LCA) in early design stages is challenged by high uncertainties due to limited product data, design variability, and a wide range of possible system configurations. These factors increase the effort required for conducting LCAs and reduce the comparability of the results. To address this, a systematic literature review was conducted to identify how Model-Based Systems Engineering and SysML elements have been applied to manage such uncertainties. The findings highlight that MBSE provides systematic mechanisms to integrate product development data and life cycle modeling, while supporting the representation of functions, variants, and product architectures. Building on these insights, a concept for methodologically integrating MBSE and LCA is proposed. SysML block elements are extended with application-specific attributes and environmental impact data in addition to their technical properties. This modular approach enables efficient modeling and comparison of product variants and life cycle alternatives, reduces redundancy, and ensures more consistent handling of methodological and data-related uncertainties in early design stages.
Schumacher et al. (Thu,) studied this question.