International Journal of Industrial Engineering, Technology & Operations Management
Vol. 3 No. 1 (2025): June 2025

Exploring the Role of Artificial Intelligence in Enhancing Lean Manufacturing and Six Sigma for Smart Factories

Nwamekwe, Charles Onyeka (Unknown)
Edokpia, Raphael Olumese (Unknown)
Igbinosa, Eboigbe Christopher (Unknown)



Article Info

Publish Date
30 Jun 2025

Abstract

The integration of Artificial Intelligence (AI) into Lean Manufacturing and Six Sigma methodologies marks a transformative advancement in smart factory operations. This research explores the pivotal role of AI in enhancing efficiency, quality, and sustainability across manufacturing processes. Case studies demonstrate how AI technologies, such as predictive maintenance and real-time monitoring, have significantly reduced downtime, optimized resource utilization, and improved product quality. AI-driven analytics and machine learning models further enable proactive decision-making, aligning Lean's waste-reduction principles and Six Sigma's quality-improvement goals. However, challenges such as high implementation costs, data privacy concerns, and workforce skill gaps impede widespread adoption. This paper discusses these barriers, proposes strategies to overcome them, and highlights opportunities to integrate AI into continuous improvement frameworks. Future research directions include developing scalable AI-driven methodologies, addressing ethical considerations, and exploring the role of AI in advancing sustainable manufacturing practices. The findings underscore AI's transformative potential to redefine Lean Six Sigma paradigms, driving innovation and operational excellence in the era of Industry 4.0.

Copyrights © 2025






Journal Info

Abbrev

ijietom

Publisher

Subject

Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

Description

International Journal of Industrial Engineering, Technology & Operations Management (IJIETOM) is an academic, double-blind peer-reviewed scientific journal published 2 times a year, i.e., June and December and focused on the diffusion of articles in the field of Industrial Engineering, Technology ...