Multi-objective optimization of material delivery for mixed model automotive assembly line based on particle swarm algorithm

To solve the real-time material delivery problems from the warehouse to workstations for the mixed model automotive assembly line in accordance with the production cycle, the dynamic material delivery method based on internet of things has been developed. The material flow and production characteristic of automotive assembly was analyzed in order to feed material properly & timely. The monitoring system of the material delivery based on internet of things was established which was composed of device layer, control layer and information management layer. The minimization multi-objective function was proposed considering materials transportation costs, materials transportation time and materials storage based on AGV and AS/RS. The hybrid particle swarm optimization (PSO) and the detail process of realization were designed. The validity of this model and algorithm was verified by a case of assembly plant materials distribution problem. Experimental results indicate that the hybrid PSO strategy show a quite promising higher performance than basic genetic algorithm for the proposed approach.