Exploring the Integration of Artificial Intelligence into Lean Six Sigma Methodologies: A Roadmap for Enhancing Manufacturing Efficiency and Quality

Căsăneanu Dascălu Nicoleta-Mihaela (), Miraute Coca Laura-Crina (), Loghin Emil Constantin () and Pislaru Marius ()
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Căsăneanu Dascălu Nicoleta-Mihaela: “Gheorghe Asachi” Technical University of Iasi-Romania, Iasi, Romania Charest University of Economic Studies, Bucharest, Romania
Miraute Coca Laura-Crina: “Gheorghe Asachi” Technical University of Iasi-Romania, Iasi, Romania
Loghin Emil Constantin: “Gheorghe Asachi” Technical University of Iasi-Romania, Iasi, Romania
Pislaru Marius: “Gheorghe Asachi” Technical University of Iasi-Romania, Iasi, Romania

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 4130-4145

Abstract: Combining artificial intelligence (AI) together with Lean Six Sigma (LSS) methods, especially the DMAIC framework (Define, Measure, Analyse, Improve, Control), has become a revolutionary way to make manufacturing processes better. This study looks at how AI and DMAIC can work together to improve operations. It focuses on how AI technologies can be added to each step of the DMAIC process. By applying artificial intelligence, prescriptive analytics, and simulation models, optimising process changes in the enhancement stage decreases cycle durations, minimises waste, and reduces related expenses. AI-powered real-time monitoring and automated alerts help the control phase stay consistent and reduce deviations by means of which it gains advantage. The research framework conceptually explains the development of DMAIC and the synergy among artificial intelligence tools. The data supports three main hypotheses H1) AI reduces variability and improves defect identification; H2) AI-driven analytics accelerates process enhancements; and H3) AI-based monitoring systems stabilise processes. Combining artificial intelligence with DMAIC provides the process of continuous growth that links operational performance to business objectives. This convergence improves manufacturing’s competitiveness by facilitating more effective data-driven decision-making, process optimisation, and quality assurance.

Keywords: Artificial Intelligence (AI); Industry 4.0; Machine Learning; Process Optimization; Lean Six Sigma Manufacturing. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:4130-4145:n:1036

DOI: 10.2478/picbe-2025-0317

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