The today’s competitive advantage of ready-made garment industry depends on the ability to improve the efficiency and effectiveness of resource utilization. Ready-made garment industry has long historically adopted fewer technological and process advancement as compared to automotive, electronics and semiconductor industries. Simulation modeling of garment assembly line has attracted a number of researchers as one way for insightful analysis of the system behaviour and improving its performance. However, most of simulation studies have considered ill-defined experimental design which cannot fully explore the assembly line design alternatives and does not uncover the interaction effects of the input variables. Simulation metamodeling is an approach to assembly line design which has recently been of interest to researchers. However, its application in garment assembly line design has never been well explored. In this paper, simulation metamodeling of trouser assembly line with 72 operations was demonstrated. The linear regression metamodel technique with resolution-V design was used. The effects of five factors: bundle size, job release policy, task assignment pattern, machine number and helper number on throughput of the trouser assembly line were studied. An increase of the production throughput by 28.63% was achieved for the best factors’ setting of the metamodel.

现成服装行业今天的竞争优势取决于提高资源利用效率和效力的能力。与汽车，电子和半导体行业相比，成衣行业长期以来一直采用较少的技术和工艺进步。服装装配线的仿真建模已吸引了许多研究人员，这是对系统行为进行深入分析并改善其性能的一种方法。但是，大多数仿真研究都考虑了实验设计不明确的问题，这些设计不能完全探索装配线设计的替代方案，也无法揭示输入变量的交互作用。仿真元模型化是装配线设计的一种方法，最近引起了研究人员的兴趣。然而，在服装装配线设计中的应用从未得到很好的探索。在本文中，演示了具有72个操作的裤子装配线的模拟元建模。使用具有解析度V设计的线性回归元模型技术。研究了五个因素：捆束大小，作业释放策略，任务分配模式，机器编号和辅助编号对裤子装配线生产量的影响。通过元模型的最佳因子设置，实现了28.63％的生产吞吐量的增长。研究了任务分配模式，机器编号和辅助编号对裤子装配线生产能力的影响。通过元模型的最佳因子设置，实现了28.63％的生产吞吐量的增长。研究了任务分配模式，机器编号和辅助编号对裤子装配线生产能力的影响。通过元模型的最佳因子设置，实现了28.63％的生产吞吐量的增长。