From Lean Six Sigma to DMAIC 4.0: Evidence-based validation of digitally enabled continuous improvement in manufacturing systems

This study investigates how digital technologies strengthen the traditional Lean Six Sigma DMAIC methodology through a large - scale improvement project in a U.S. sheet metal manufacturing facility. It presents empirical evidence of digitally enabled practices later formalized as DMAIC 4.0 within a real operational environment. A retrospective case study examined DMAIC implementation integrating Direct Numerical Control (DNC) systems, CAD/CAM automation, standardized CNC tooling, and Minitab - based statistical analysis. The evaluation used time studies of 15,940 parts, representing 46.9% of annual production, achieving a 95% confidence level with a margin of error below 3%. Performance improvements were verified through statistical testing and validated financially using Sarbanes - Oxley - compliant reporting based on payroll, production, and material records. Results showed significant operational gains: programming time decreased by 86.45%, material efficiency improved by 14.4%, weekend overtime was eliminated, throughput increased, and capacity equivalent to 9.1 full-time positions was recovered. The project generated finance - validated annual savings of $1,263,388 across seven improvement categories. Improvements remained sustainable for several years and were successfully transferred following facility relocation. The findings provide rare empirical evidence of digitally supported DMAIC implementation and offer convergent validation that industry practice anticipated principles now formalized as DMAIC 4.0.

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Publication Details

Journal
Quality Management Journal
Published
2026-08-21
DOI
https://doi.org/10.1080/10686967.2026.2717194
Primary Topic
Digital Transformation in Industry
Type
article
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article

From Lean Six Sigma to DMAIC 4.0: Evidence-based validation of digitally enabled continuous improvement in manufacturing systems

Mohammed Ali, Randell Farley
Quality Management Journal
Digital Transformation in Industry
article

From Lean Six Sigma to DMAIC 4.0: Evidence-based validation of digitally enabled continuous improvement in manufacturing systems

Mohammed Ali, Randell Farley
article en

Abstract

This study investigates how digital technologies strengthen the traditional Lean Six Sigma DMAIC methodology through a large - scale improvement project in a U.S. sheet metal manufacturing facility. It presents empirical evidence of digitally enabled practices later formalized as DMAIC 4.0 within a real operational environment. A retrospective case study examined DMAIC implementation integrating Direct Numerical Control (DNC) systems, CAD/CAM automation, standardized CNC tooling, and Minitab - based statistical analysis. The evaluation used time studies of 15,940 parts, representing 46.9% of annual production, achieving a 95% confidence level with a margin of error below 3%. Performance improvements were verified through statistical testing and validated financially using Sarbanes - Oxley - compliant reporting based on payroll, production, and material records. Results showed significant operational gains: programming time decreased by 86.45%, material efficiency improved by 14.4%, weekend overtime was eliminated, throughput increased, and capacity equivalent to 9.1 full-time positions was recovered. The project generated finance - validated annual savings of $1,263,388 across seven improvement categories. Improvements remained sustainable for several years and were successfully transferred following facility relocation. The findings provide rare empirical evidence of digitally supported DMAIC implementation and offer convergent validation that industry practice anticipated principles now formalized as DMAIC 4.0.

Quality Management Journal
The University of Texas at Tyler (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Digital Transformation in Industry
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From Lean Six Sigma to DMAIC 4.0: Evidence-based validation of digitally enabled continuous improvement in manufacturing systems — Mohammed Ali, Randell Farley · Quality Management Journal (2026) | TGRS Research Map | TGRS