Enhancing Process Planning in the Automotive Industry: Extracting Procedural Knowledge from Assembly Operation Descriptions using Large Language Models

The non-standardized, human-written assembly descriptions have been a long-standing obstacle in the automotive assembly industry, making it difficult to use these data in the planning stage. The paper presents a standardization method based on Large Language Models (LLMs), focusing on consistency and clarity. This approach does not only streamline the planning processes but also facilitates the benchmarking of productivity and process quality across different individual parts and assembly lines, thus enabling comprehensive efficiency analysis and ultimately leading to more informed decision-making. Our method was evaluated at a German OEM in the automotive sector, demonstrating its practical applicability and effectiveness.