Design and scheduling of garment assembly line using simulation-based optimization : A case Study at NYTIL, Jinja, Uganda

Abstract

Ready-made garment manufacturing industries are characterized by high variability of the processing times, short product life cycle and huge number of employed resources which contribute to low productivity. Thereby, optimal garment assembly line design is very crucial for achieving high productivity, increasing line efficiency and improving decision making at both levels of production planning. Assembly line design problem has gained attention of many researchers in the past years whereby a number of researches have been done on garment assembly line balancing problem with simulation technique. However, very few have used simulation-based optimization technique to address the design problem. The main objective of study was to design an optimal trouser assembly line with the parameters’ settings that maximizes the production throughput. Specifically, the study aimed to analyze current-state of the existing trouser assembly line and develop its simulation model, to generate design alternatives, and to determine the global optimal design alternative. The current-state of existing garment production facility was analyzed using industrial engineering tools which include brainstorming, fishbone diagram, ABC analysis, process mapping, and time study. Then, the discrete event simulation model of the trouser assembly line was developed using Arena simulation software and was validated using one-sample T-test. The trouser assembly line simulation model was accepted at T-value of -0.20 and P-value of 0.842. Sixteen design alternatives were generated by performing experiments on the design points derived from the design of experiment and the metamodel was developed using liner regression method. The metamodel was validated using significant test at alpha value 0.05 and the best setting was adopted as the initial solution for the optimization process. Metaheuristic optimization was performed on the simulation metamodel with the help of OptQuest for Arena to search for the global best design alternative. The effects of bundle size, job release policy, task assignment pattern, number of machines and number of helpers on the production throughput were analyzed. Only two factors; machine numbers and helper numbers and their interaction have significant effect on the throughput. The comparison with the existing trouser assembly line design was made based on the production throughput. The result shows 28.63% increase in the throughput for the trouser assembly line at metamodel design and the overall increase of 53.63% for the optimal design. Consequently, the production efficiency increased to 79.75% and 95.25% at metamodel and optimal design stages, respectively. From the results of the study, it was concluded that simulation-based optimization via design of experiment is suitable for giving an insight of garment assembly line and achieving its optimal design. In the further study, simulation models of garment assembly line can be developed by considering other design parameters which include machines failure and line supervisor functions. In addition, further study can be done with different approaches such as using machine learning and more complex experimental design for developing the metamodels.