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March 3, 2026International Journal of Productivity and Performance Management2 citations

Implementation of VSM, simulation and DMAIC methodology for the productivity enhancement of sewing operations in the apparel industry

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HNHassan NawazNational University of Science and TechnologySAShamraiz AhmadMRMuhammad Huzaifa Raza

Key Points

  • Productivity increased by 9.3%, while lead time was reduced by 73%, highlighting improved efficiency in sewing operations.
  • Value stream mapping and discrete event simulation exposed several non-value-added activities that hindered production efficiency.
  • The use of Lean Six Sigma methodology effectively eliminated identified inefficiencies, optimizing overall production processes.
  • Implementation in a single denim manufacturing scenario suggests potential for broader application across similar labor-intensive industries.

Abstract

Purpose Textile industries in developing countries face the major challenge of fulfilling customer demand at competitive prices. Therefore, it becomes inevitable for industry to reduce its production costs by minimizing process waste to survive in the global market. Design/methodology/approach This research focuses on the identification and elimination of Lean wastes from the sewing production lines in the apparel industry through value stream mapping supported by “Define, Measure, Analyze, Improve and Control” (DMAIC) methodology of Six Sigma. The analysis has been further supported by discrete event simulation (DES) to investigate the current situation and map the future state of the system. The analytic hierarchy process, integrated with the Grey relational analysis approach, is practiced exploring the best optimum solution from the various feasible solutions suggested by DES. Findings VSM and DES highlighted the multiple non-value-added (NVA) activities, including the high level of work in process within the production line, unnecessary operations, bottleneck workstations and manual operations that could be automated with less effort. Lean Six Sigma (LSS) has proven to be an effective method for eliminating the identified NVA activities from the production line. Quantitative analysis showed an improvement in productivity of 9.3% and a lead time reduction of 73%. Additionally, the amount of clothing produced per shift has increased by 6.8%, which in the initial situation was not even enough to meet the daily demand from customers. Research limitations/implications By adapting the integrated LSS, DES and multi-criteria decision-making paradigm to other labor-intensive industries, this study increases its generalizability in the context of Industry 4.0 and creates opportunities for future research. Its concentration on a single denim manufacturing scenario, however, may limit its wider applicability in the absence of additional validation across pertinent industries. Originality/value The proposed methodological framework, based on different industrial engineering tools and techniques, provides a strategic roadmap to not only the apparel industry but also the related industries that are suffering from low productivity and high lead time.

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Cite This Study

Nawaz et al. (2026) studied this question.

synapsesocial.com/papers/69a75b78c6e9836116a22d3ehttps://doi.org/10.1108/ijppm-03-2025-0206
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