Enhancing garment manufacturing process efficiency: a DMAIC case study for process improvement

This study applies the Six Sigma DMAIC methodology to reduce high defect rates in the stitching process of garment manufacturing. Focused on a leading firm producing 5-pocket denim jeans over 18 days, it systematically identifies and addresses defects like pleat/puckering, slip stitch, and uneven stitch, primarily caused by operator errors, machine malfunctions, and inadequate training. Using tools like Pareto charts and cause-and-effect diagrams, interventions such as operator training, machine maintenance, and process standardisation reduced the defect per million opportunities (DPMO) from 3363 to 228, raising the sigma level from 4.2 to 5.01. The project also improved worker safety, cost management, and operational efficiency. This successful implementation of DMAIC not only resolved immediate quality issues but also provided a scalable model for future improvements in garment manufacturing, demonstrating the economic benefits of defect reduction and process optimisation.

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Publication Details

Journal
International Journal of Productivity and Quality Management
Published
2025-01-01
DOI
https://doi.org/10.1504/ijpqm.2025.148017
Citations
1
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
2.48
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article

Enhancing garment manufacturing process efficiency: a DMAIC case study for process improvement

1 citations
International Journal of Productivity and Quality Management
Geochemistry and Geologic Mapping
2.48
article

Enhancing garment manufacturing process efficiency: a DMAIC case study for process improvement

article en
1 citations

Abstract

This study applies the Six Sigma DMAIC methodology to reduce high defect rates in the stitching process of garment manufacturing. Focused on a leading firm producing 5-pocket denim jeans over 18 days, it systematically identifies and addresses defects like pleat/puckering, slip stitch, and uneven stitch, primarily caused by operator errors, machine malfunctions, and inadequate training. Using tools like Pareto charts and cause-and-effect diagrams, interventions such as operator training, machine maintenance, and process standardisation reduced the defect per million opportunities (DPMO) from 3363 to 228, raising the sigma level from 4.2 to 5.01. The project also improved worker safety, cost management, and operational efficiency. This successful implementation of DMAIC not only resolved immediate quality issues but also provided a scalable model for future improvements in garment manufacturing, demonstrating the economic benefits of defect reduction and process optimisation.

International Journal of Productivity and Quality ManagementVol. 45(4)
NED University of Engineering and Technology (PK), Royal Holloway University of London (GB), University of Regina (CA)
Openalex Percentile: Top 7%
Geochemistry and Geologic Mapping
2.48
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Enhancing garment manufacturing process efficiency: a DMAIC case study for process improvement · International Journal of Productivity and Quality Management (2025) | TGRS Research Map | TGRS