An integrated MCDM-Simulation approach to study the effect of lot-splitting in a large-scale assembly job shop: a case study

The impact of lot-splitting on performance measures of the assembly job shop has been investigated in this study. The problem considered in this study includes 10 different products comprising 149 components, with 14 to 16 components in each product. Every component undergoes 1 to 8 operations. A total of 206 operations is to be completed using 28 machines. Discrete Event Simulation (DES) models were developed considering static and dynamic job arrival scenarios to evaluate makespan, mean flowtime and tardiness. TOPSIS-based MCDM with different normalization procedures is proposed to prioritize jobs. The performance of MCDMs is compared with the known priority rules in the literature. Among the normalization techniques, the linear normalization (Max-Min) achieves the best results for minimizing mean flowtime and mean tardiness. The linear normalization (Max) variant is the most effective in reducing maximum tardiness. Lot splitting resulted in improved makespan, mean flowtime and tardiness by 16%, 20% and 39%, respectively. Statistical analysis using ANOVA and Tukey’s HSD tests was conducted to analyze the significance of the results produced by the proposed MCDMs.