Leveraging supplier material data to inform LCA modelling and resource assessment in the automotive industry

Licentiate thesis, 2023

This thesis investigates the application of supplier material composition data from the automotive industry's International Material Data System (IMDS) to inform sustainability assessments. A methodology is developed to systematically extract and process IMDS data for use in life cycle assessment (LCA) modelling. The implications of using IMDS data at varying levels of aggregation and completeness on the accuracy of LCA results are quantitatively evaluated through an LCA case study on an automotive engine. Compared to a highly detailed reference model, simplified modelling options reduced workload but compromised accuracy, especially for impacts related to resource use. A material mass cut-off of one percent of weight maintained reasonable precision while significantly decreasing effort. Decreasing the number of substances representing each material largely affected scores for most impact categories except a few, including the climate change category. Excluding manufacturing data notably impacted greenhouse gas emissions.

Additionally, this thesis performs an in-depth compositional analysis focusing on metals present in two vehicle "gliders" (the car excluding the powertrain) with distinct equipment levels. Over 50 metals are documented, and their contributions to short and long-term metal scarcity examined. Gold, copper, bismuth, lead, molybdenum, and certain rare-earth metals (REMs) face substantial supply risks. The analysis of metals across the gliders subsystems and components indicates that equipment levels significantly affect short-term supply risks for some metals. Entropy analysis is also used to gather insights into the effectiveness of different substitution and secondary metal recovery strategies revealing significant challenges for the recovery and substitution of certain metals like copper and rare earths.

Overall, this thesis demonstrates the potential of leveraging IMDS data to expedite sustainability assessments in the automotive industry. However, balancing model complexity and precision remains essential. The extensive reliance of vehicles on diverse metals, even excluding the powertrain, highlights the sector's substantial resource dependence. This underscores the need for sustainable metal management in automotive manufacturing.