DMAIC 4.0 in Action: introducing MSA 4.0 and Poka Yoke 4.0

The rise of Big Data and Industry 4.0 has significantly increased data volumes and process complexity, yet DMAIC (Design tools have evolved little to incorporate advances in data science. This Action Research study applies the DMAIC 4.0 framework, operationalizing the integration of Lean Six Sigma with Industry 4.0 technologies. Two novel contributions are presented: MSA 4.0, an AI-enhanced method for scalable measurement system analysis with large datasets, and Poka Yoke 4.0, a predictive, real-time error-prevention approach. Applied to the manual welding process in a German manufacturing company, these innovations achieved an 86% reduction in defective weld area and an 84% reduction in defect counts, with a projected ROI of 2 years. Beyond the case evidence, this study contributes a replicable strategy by combining DMAIC with the CRISP-DM model, fostering collaboration between data scientists and LSS practitioners. Although the findings are limited to a single case study, the research demonstrates how DMAIC 4.0 can bridge the gap between traditional process improvement and digital transformation. It offers a transferable pathway for OPEX professionals and researchers to strengthen accuracy, error-proofing, and decision-making in the era of Big Data and Industry 4.0 across diverse organizational contexts.