Optimal Assignment of Machine Operators to Enhance Productivity and Skill Efficiency in Assembly Lines in Apparel Industry Using Two-Phase Integer Linear Programming Model: A Case Study

Abstract

Assembly line balancing (ALB) in the apparel industry is crucial for optimizing production efficiency. It requires an optimum assignment technique for machine operators (MOs) based on their skills and availability to minimize production delays and enhance productivity. This study aims to optimize the line layout and production throughput by applying a bottleneck-oriented resource allocation framework that combines the Rank Positional Weight Method (RPWM) with a two-phase IntegerLinear Programming model (ILPM). Once the line layout is determined by the RPWM, the next stage is to assign MOs to operations by solving a two-phase ILPM. In the first phase, an ILPM is applied to maximize the total production rate by assigning MOs to operations, based on their efficiency, identifying bottleneck operations which contribute to the lowest production rate. In second phase, the total skill level of the assembly line is minimized. The predetermined bottleneck production rate is used as an indicator, ensuring that the production rate which is maximized in the first phase is kept fixed.The reassignment of the remaining MOs is based on their skill levels, while the bottleneck operations and operators are kept aside in the second phase. The bottleneck operation, identified in the first phase, ensures that the most efficient MOs are assigned where needed, while other operations are conducted by MOs based on a compromise solution between their skill levels and availability. This approach emphasizes the importance of line balancing and operator assignment in the apparel industry and determining the ideal number of MOs needed to perform the set of operations. Additionally, thisproposed method can be adopted to any production line with necessary modifications.