Abstract:
This thesis investigates the development of a pre-production sample of T-shirts for bulk production, focusing on optimizing various stages of the garment manufacturing process to enhance efficiency, quality, and cost-effectiveness. The research delves into the complexities involved in T-shirt production, from material selection and pattern making to cutting, sewing, and finishing, with an emphasis on the importance of pre-production samples in securing bulk orders. The study applies optimization techniques such as Lean Manufacturing, Time Study, and Line Balancing to streamline operations, reduce waste, and improve worker productivity. By analyzing production efficiency and implementing quality control measures, the research identifies key areas where improvements can be made, particularly in fabric handling, cutting accuracy, and labor allocation. The results demonstrate that adopting automation and optimizing work processes lead to higher productivity, reduced costs, and improved product quality. Recommendations for future research include exploring sustainable practices and integrating new technologies like AI to further enhance production efficiency. This study provides valuable insights for manufacturers seeking to improve the accuracy and efficiency of pre-production sample development, ensuring successful transitions to bulk production.
