Lean waste prioritisation and reduction in the apparel industry: application of waste assessment model and value stream mapping

Abstract

Manufacturing industries implement lean production tools to improve their production efficiencies. Improving production efficiency is vital in the apparel industry because product cycles and lead times are getting shorter and shorter. The purpose of this study was to improve the performance of a shirt manufacturing company through the implementation of value stream mapping (VSM) along with some other lean tools. Data were collected through stop-watch-based time studies and structured questionnaires. On the one hand, the current state value stream map was created and its performance was examined. On the other hand, the ranks of the seven lean wastes were determined, and process activity mapping was used to analyse the wastes furthermore. Then, layout improvement and 5S were implemented to reduce the main wastes, and the future state value stream map was developed. Analysis of the wastes resulted in motion, inventory and overproduction as the main wastes, while materials and machines were found to be the main sources of lean wastes. The main results of lean implementation showed 74.30%, 30.95%, 71.1% and 27.02% reductions in work-in-process inventory, value-added time, lead time and standard minute value, respectively. The findings of this study support the applicability of VSM in the apparel industry.

Keywords:

• Waste assessment
• prioritisation
• reduction
• apparel industry
• value stream mapping
• VSM
• lean tools

Reviewing Editor:

• Zude Zhou, Wuhan University of Technology, China

Subjects:

• Textile Manufacturing
• Engineering Management
• Production Engineering
• Industrial Engineering & Manufacturing

Acknowledgements

The authors are thankful to the Ethiopian Institute of Textile and Fashion Technology, Bahir Dar University for covering the expenses of the study through the fund.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was conducted under the centre of excellence for the higher education and TVET program Ethiopia-phase 3, PE479 higher education, KFW project number 51235 and BMZ number 201166305.

Notes on contributors

Berihun Bizuneh

Berihun Bizuneh is an Associate Professor at the Ethiopian Institute of Textile and Fashion Technology, Bahir Dar University, Bahir Dar, Ethiopia. He holds a PhD in Industrial Management from the National Taiwan University of Science and Technology (Taiwan, 2019), an MBA in Marketing from Mekelle University (2011) and a BSc in Textile Engineering from Bahir Dar University (2007). He has broad experience in research on industrial management with a focus on production management, quality control, and data mining applications. Berihun possesses teaching experience in textile economics, quality control, product development, project management, operations management, and operations research.

Rahmet Omer

Rahmet Omer is a Lecturer at the Department of Garment Engineering, Wolkite University, Wolkite, Ethiopia. She holds an MSc in Fashion Technology (2022) and a BSc in Garment Engineering from Bahir Dar University, Bahir Dar, Ethiopia. She has teaching experience in lean manufacturing systems, cutting technology, pattern making, garment construction, high-performance products, production planning and control, apparel trim and accessories, and statistical applications in the garment industry.