Balancing Two-Sided Multi-Manned Assembly Lines Using Genetic Algorithm

Abstract

Two sided assembly lines are used for large sized products where assembly tasks are performed by two workers on both sides. Multi-manned lines are mainly used in the assembly of relatively large products, with a number of workers moving around the product performing assembly tasks. This movement may lead to interference and congestion of man and material. In this paper a new line configuration is investigated by combining the two types of lines in what is designated as Two-Sided Multi-Manned (TSMM) assembly line. The proposed configuration benefits from the advantages of both lines by proposing four workers; two on each side, avoiding interference of the work and reducing the assembly stations.A model based on genetic algorithm was developed to balance the proposed TSMM line under the objectives of minimizing the number of workers and the number of mated-stations. A new method for generating the initial population is proposed leading to remarkably faster convergence of the solution. A controlling parameter is introduced to enable the tradeoff between the number of workers and the number of mated stations, adding flexibility to the line design. Results reveal that the proposed model gives competitive results to genetic algorithm and particle swarm optimization in the two-sided assembly line benchmark problems. It converges to a final solution in considerably less number of iterations. The application of the TSMM line concept results in considerable reduction in the number of mated stations with space saving up to 50% for the same number of workers.