Reducing inventory waste and improving traceability of small fabric rolls in a knitted textile factory: A lean-based case study

By the end of 2024, the garments industry in Bangladesh which contributing to its economy over $50 billion in exports sector, faces significance challenges in inventory management, particularly in traceability of small fabric rolls. In this case study we investigate a Bangladeshi garments factory supplying major global brands such as H&M, PUMA, and Hugo Boss, where traditional inventory system and poor traceability of rolls often lead to wastage, re-knitting, delays in production, and delivery commitment failures. This study aims to find out the root causes of inventory inefficiency and determine some inventory KPIs (key performance index) that will improve efficiency by applying three lean manufacturing tools in the inventory like, 5S, Value Stream Mapping (VSM), and ABC analysis. We gathered a lot of data about our inventory and looked at it to sort it by contribution and consumption priority, find problems with our current processes, and measure how much better things got using key metrics. The application of lean tools led to mentionable improvements in key performance metrics. Retrieval time decreased by 30%, waste generation reduced by 25%, and machine idle time dropped by 45%. These improvements were possible by organized inventory management, and optimal scheduling, resulting in a more streamlined production process, with less retrieval time, less waste, and enhanced machine efficiency. The study provides a data-driven framework for inventory improvement, demonstrating the effectiveness of lean tools in addressing inefficiencies in garment factories, particularly in emerging economies.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-30
DOI
https://doi.org/10.5281/zenodo.17263325
Primary Topic
Economic, financial, and policy analysis
Type
article
Field-Weighted Citation Impact
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article

Reducing inventory waste and improving traceability of small fabric rolls in a knitted textile factory: A lean-based case study

Zenodo (CERN European Organization for Nuclear Research)
Economic, financial, and policy analysis
article

Reducing inventory waste and improving traceability of small fabric rolls in a knitted textile factory: A lean-based case study

article en

Abstract

By the end of 2024, the garments industry in Bangladesh which contributing to its economy over $50 billion in exports sector, faces significance challenges in inventory management, particularly in traceability of small fabric rolls. In this case study we investigate a Bangladeshi garments factory supplying major global brands such as H&M, PUMA, and Hugo Boss, where traditional inventory system and poor traceability of rolls often lead to wastage, re-knitting, delays in production, and delivery commitment failures. This study aims to find out the root causes of inventory inefficiency and determine some inventory KPIs (key performance index) that will improve efficiency by applying three lean manufacturing tools in the inventory like, 5S, Value Stream Mapping (VSM), and ABC analysis. We gathered a lot of data about our inventory and looked at it to sort it by contribution and consumption priority, find problems with our current processes, and measure how much better things got using key metrics. The application of lean tools led to mentionable improvements in key performance metrics. Retrieval time decreased by 30%, waste generation reduced by 25%, and machine idle time dropped by 45%. These improvements were possible by organized inventory management, and optimal scheduling, resulting in a more streamlined production process, with less retrieval time, less waste, and enhanced machine efficiency. The study provides a data-driven framework for inventory improvement, demonstrating the effectiveness of lean tools in addressing inefficiencies in garment factories, particularly in emerging economies.

Zenodo (CERN European Organization for Nuclear Research)
Rajshahi University of Engineering and Technology (BD), University of Rajshahi (BD)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Economic, financial, and policy analysis
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