Optimizing Machining Process Performance Using Lean Six Sigma: A Case Study

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Article Type: Research Article
Issue: Vol. 1 No. 1 (2025)
Published: 05 November 2025
Pages: 52-81

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Gomaa, A. H. (2025). Optimizing Machining Process Performance Using Lean Six Sigma: A Case Study. Transnational Supply Chain Research, 1(1), 52-81. https://doi.org/10.65773/tscr.1.1.46

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Authors

Attia Hussien Gomaa
Mechanical Engineering Department, Faculty of Engineering. Shubra, Benha University, Cairo, Egypt

Abstract

To sustain competitiveness, companies continuously improve quality, productivity, and customer satisfaction, with Lean Six Sigma recognized as a key methodology for driving enduring operational excellence. This study examines the implementation of Lean Six Sigma (LSS) in machining operations, addressing key challenges such as (1) the lack of a unified, adaptable LSS framework tailored to machining processes, (2) limited empirical validation in industrial contexts, and (3) insufficient assessment of critical performance metrics, including quality, productivity, and customer satisfaction. To address these gaps, a structured, integrated LSS framework is proposed, combining Lean’s waste-elimination principles with Six Sigma’s data-driven methodologies for defect reduction and process variation control. The framework leverages robust measurement systems, statistical process analysis, and machining parameter optimization, providing a systematic, evidence-based approach to identify, prioritize, and implement process improvements.The framework was validated through a three-month case study in a leading spare parts manufacturing company in Egypt. Implementation resulted in notable improvements: product quality increased from 85% to 89%, sigma level rose from 2.5 to 2.7, processing time decreased from 645 to 370 hours/ton, overall equipment effectiveness (OEE) improved from 75% to 81%, value-added activities increased from 50% to 54%, and customer satisfaction rose from 87% to 89%. These results confirm the framework’s effectiveness in enhancing process stability, operational efficiency, and product performance, providing actionable guidance for engineers, managers, and researchers seeking to institutionalize continuous improvement in machining operations.Ultimately, the proposed LSS framework serves as a comprehensive reference for production managers, organizational leaders, and researchers across diverse industrial sectors, offering structured and evidence-based guidance before initiating continuous process improvement initiatives.

Keywords:
lean six sigma (LSS), DMAIC framework, machining process optimization, operational excellence, continuous improvement, problem solving methodology

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References

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