A Comparative Evaluation of Line Balancing Methods to Enhance Sewing Line Performance

The textile and apparel industry of Bangladesh is the backbone of its economy, although this industry faces challenges in optimizing productivity and resource utilization due to inefficient workflows and bottlenecks. This study evaluates and compares three assembly line balancing methods, the Largest Candidate Rule (LCR), Rank Positional Weighted (RPW) Method, and Moodie Young Method with the Existing Method in a sewing line in an apparel industry. The analysis focuses on key performance metrics, including balance accuracy, resource utilization, bottleneck reduction, and material flow index (MFI). Results indicate that the Moodie Young Method demonstrates the highest resource efficiency, requiring only 39 machines and minimizing double machine workstations while achieving a moderate balance accuracy of 83%. In comparison, LCR and RPW achieve the highest balance accuracy of 90% but each requires a high number of 52 machines. The Existing Method exhibits significant inefficiencies, with the lowest balance accuracy (78%) and the highest number of bottlenecks (9). This nobility of the research is that it introduces MFI as a critical metric to evaluate material flow efficiency to ensure workflow continuity. Additionally, this approach highlights the effectiveness of heuristic techniques in balancing operational efficiency and cost-effectiveness. The study’s outcomes provide a comparative analysis of 3 assembly line balancing methods in apparel industries, with potential applications in other manufacturing sectors. Future research could incorporate external variables and real-time data for further optimization.