The Future of Six Sigma- Integrating AI for Continuous Improvement

Anitej Chander Sood; Konika Singh Dhull

doi:10.55524/ijirem.2024.11.5.2

Abstract

This study explores the incorporation of Artificial Intelligence (AI) into traditional Six Sigma's DMAIC (Define, Measure, Analyze, Improve, Control) methodology to enhance continuous process improvement and achieve significant economic growth across industries. AI’s data analysis, machine learning algorithms coupled with real-time insights can expedite problem identification in manufacturing processes before they become substantial issues – eliminating the need for human oversight by proactively identifying potential errors or bottlenecks - this reduces wastage and optimizes resource utilization. Coupling AI’s predictive capabilities with Six Sigma's systematic approach not only boosts productivity but also ensures robust quality control standards are met – leading to continuous nonstop improvement in various sectors globally, particularly supply chain management where operational efficiency is critical for success and sustainability. By enhancing resource allocation effectiveness through AI automation while reducing waste generation via predictive analytics - this integration holds the key towards achieving both economic growth objectives alongside environmental stewardship as complementary facets of successful business strategies in today's global marketplace, fostering a future where operational excellence and sustainability go hand-in-hand.

Keywords

Artificial Intelligence (AI), Continuous Improvement, DMAIC (Define, Measure, Analyze, Improve, Control), Industry 4.0, Machine Learning, Predictive Maintenance, Process Optimization, Six Sigma

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Cites this article as

A. C. Sood, K. S. Dhull, "The Future of Six Sigma- Integrating AI for Continuous Improvement ", International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-11, Issue-5, Page No-8-15, 2024. Available from: https://doi.org/10.55524/ijirem.2024.11.5.2