Background: The plastics manufacturing industry, particularly in water tank production, faces significant inefficiencies in material handling. Manual unpacking is the primary bottleneck, operating at 99% utilization (a level that severely restricts overall production flow) resulting in low output of only 378 units per shift. This critical constraint highlights the urgent need for process optimization to improve throughput and operational efficiency. Objective: This study aims to evaluate and compare two material handling system scenarios using Discrete Event Simulation (DES) based on Arena software, namely a semi-automated system with an automatic unpacking machine and a fully automated system with an unpacking robot, using a manual system as the base model for comparison. Methods: Primary data were obtained through direct observation and time studies at a medium-scale plastic manufacturing plant in Indonesia. Results: Simulation results show that the automatic unpacking machine scenario provides the most balanced improvement, with a 58% decrease in system waiting time, a 65% reduction in work-in-process (WIP), and a 44% increase in throughput compared to existing conditions. Meanwhile, the unpacking robot reduced waiting time by 97% in the unpacking process but created a new bottleneck in the downstream process. Conclusion: This study confirms that partial automation through unpacking machines is the optimal solution for medium-scale plastic manufacturing companies to improve operational efficiency while maintaining a balanced level of resource utilization.
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