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Subject Area

Textile Engineering

Article Type

Original Study

Abstract

The textile and apparel sector has always held significant strategic value for the economies of numerous developing countries. These industries represent vital components of manufacturing and exports, playing a major role in employment opportunities. Within the realm of garment production, a strong emphasis on quality is maintained throughout the entire process, starting from sourcing raw materials and extending to the final stages of garment completion.

This research undertaking involves a comprehensive analysis, classification, and evaluation of defects in fabrics and garments. Frequencies and distributions of these defects are being looked after with great caution. To enhance product quality, the application of straightforward quality frameworks is of utmost importance. The proposed approach involves utilizing effective statistical tools like Pareto diagrams and Cause-and-Effect diagrams. By adopting this strategy, it becomes possible to systematically reduce variability and rectify defects. Consequently, this methodology has the potential to be consistently applied, resulting in a noteworthy enhancement of garment quality across production cycles. Furthermore, utilizing statistical instruments such as the probability mass function (PMF) obtained from the binomial distribution is of immense value for evaluating the probabilities of defects’ occurrence. An illustrative real-world instance shows its utility in forecasting defect incidents, supporting manufacturers in approximating defective sections, and directing endeavors to elevate quality.Top of Form

Keywords

Garment, Quality, Defects, Pareto, Cause-and-Effect, PMF

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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