Scenario-based discrete-event simulation for production bottleneck identification and capacity optimization in garment small and medium enterprises - Dwi Adi Purnama; Zelania In Haryanto (Journal Industrial Servicess, 2026)
This study addresses production system inefficiencies in garment manufacturing, particularly related to flow imbalance, bottlenecks, and low throughput in multi-stage production lines. A discrete-event simulation (DES) model was developed using FlexSim 6.0 to evaluate material handling and processing performance in a six-stage garment production system. The model was validated using statistical tests, confirming its ability to represent real-world system behavior. The results indicate that severe capacity imbalance at the sewing stage leads to critical system inefficiencies, characterized by extremely high blocking rates (up to 92.10%), high resource idleness in upstream processes, and low throughput performance, with only 60 units produced from 760 input materials. To address this issue, multiple improvement scenarios were evaluated through simulation-based experimentation. The findings show that increasing capacity at key bottleneck stages significantly improves system performance, with the best scenario increasing daily output to 171–184 units. Statistical analysis confirms that the improvements are significant across all scenarios. This study contributes methodologically by demonstrating a simulation-based framework for identifying bottlenecks, evaluating system performance, and testing capacity improvement strategies in garment production systems. Unlike case-specific problem-solving approaches, the proposed framework provides a generalized analytical approach applicable to similar multi-stage manufacturing environments. The findings highlight the importance of capacity balancing and system-level optimization in improving production efficiency. The proposed approach offers practical insights for production system design and supports the application of simulation as a decision-support tool in industrial engineering contexts.