Enhancing the labor division in the balancing of apparel assembly lines with parallel workstation through an improved ant colony algorithm

Abstract

In order to overcome the inefficiency of labor division and management confusion in garment manufacturing assembly lines when introducing parallel workstations, an improved ant colony optimization (IACO) algorithm with multi-pheromones is proposed in this paper, which provides a new strategy to improve the match degree of operators and tasks in garment assembly line with parallel workstations. In proposed IACO, the first pheromone is set for ant to improve the efficiency of lines efficiency by balancing the workload allocation among workstations, and the second pheromone determines whether to create parallel workstations by valuing the complexity distribution of tasks. Existing real data of a garment manufacturing factory is used to verify the effective of IACO and the result shows that IACO contributes to a smooth work flow, and simultaneously reduce the efficiency loss of labor divisions (ELLD). Moreover, experiments are conduct to explore the trade-off relation between labor division and line arrangement efficiency when introducing parallel workstations. And based on the relation, strategies to create parallel workstations in the assembly line is provided for garment factories with different staff qualities for different apparel products.