Interdisciplinary Production Risk Exploration: A Grounded Approach to Integrate Data- and Knowledge-Driven Analytics

Abstract

In the age of disruption, rapidly evolving conditions in manufacturing necessitate effective capabilities to identify and manage production risks. Some of the most challenging risks in this context emerge from interdisciplinary issues that cannot easily be addressed by methods and tools within a single discipline, such as mechanical, electrical, or automation engineering. To enable comprehensive analysis of such interdisciplinary production risks, we propose Interdisciplinary Production Risk Exploration (IPRE) as a structured, data-driven methodology. IPRE integrates data with fragmented knowledge of production engineers, process experts, and data analysts across domains to identify and characterize production risks to guide data-analytic processes. We evaluate the approach in a case study on a hairpin production process at Volkswagen AG. The study results show that validated hypotheses can effectively focus data analysis on the most critical quality factors and thereby significantly reduce the number of quality criteria that need to be analyzed. Furthermore, the study shows how IPRE can be effectively integrated into the production process.