Enhancing Operational Efficiency in Resource-Constrained Apparel SMEs through Simulation-Based Process Standardization

This study examines the use of Discrete Event Simulation as a strategic tool for operational optimization in small and medium-sized enterprises in the textile sector, focusing on a women’s boxer shorts production line. The research addresses common inefficiencies in resource-constrained, high-variability environments, including task fragmentation, unbalanced workloads, and excessive cycle time variability. A validated simulation model was developed using Arena® software, supported by time and motion studies, probability distribution fitting, and field data. Two improvement scenarios were evaluated: (1) the integration of auxiliary labor at bottleneck stations and (2) the standardization of operating procedures to reduce process variability. Simulation results indicate that Scenario 1 produced negligible throughput improvements, whereas Scenario 2 increased average shift production by 31%, reduced variability, and enhanced production stability. Statistical significance was confirmed using ANOVA on average shift output with 30 independent replications per scenario (p < 0.05), complemented by Tukey’s test. Model validity was further supported by a deviation within ±4% relative to real system performance. These results highlight the value of simulation-based experimentation for improving efficiency, supporting data-driven decision-making, and enhancing competitiveness in modular textile manufacturing systems without substantial capital investment.