Abstract Modeling and simulation are essential tools for understanding and optimizing production systems, particularly in the garment manufacturing industry. This study focuses on optimizing the production line at MAA Garment by applying discrete-event simulation (DES) combined with lean manufacturing tools. Excessive queuing at certain workstations significantly increased the overall cycle time. The study uses both primary and secondary data sources: primary data were gathered through interviews with key personnel and time studies, while secondary data were obtained from company records and related research. The simulation process included problem identification, data collection, model formulation, verification and validation, and experimentation. After identifying lean wastes through simulation, lean tools such as line balancing, layout redesign, and quality-at-the-source were implemented. The results show a reduction in cycle time from 6.99 minutes to 5.02 minutes, a substantial increase in line productivity from 31.57–70.58%, an improvement in line efficiency from 45.98–73.82%, and a doubling of the daily production target output from 600 to 1200 units. Furthermore, the number of operators was reduced from 19 to 17, enhancing operational efficiency. This study demonstrates how combining simulation with lean practices can significantly improve production performance and provides valuable insights for optimizing manufacturing processes in similar industries.
Gessesse et al. (Thu,) studied this question.
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