A Discrete Particle Swarm Optimization Approach to Optimize the Assembly Sequence of Mechanical Product

The aim of assembly sequence planning (ASP) is to achieve the best assembly sequence which assembly cost and time used is less. The geometrical feasibility of an assembly sequence is validated by the interference matrix of the product. The number of assembly tool changes and the number of assembly operation type changes are considered in the fitness function. To establish the mapping relation between ASP and particle swarm optimization (PSO) approach, some definitions of position, velocity and operator of particles are proposed. The difference of the proposed discrete PSO (DPSO) algorithm with the other algorithm is the emphasis on the geometrical feasibility of the assembly sequence. The geometrical feasibility is verified at the first and the every iteration. The performance and feasibility of the proposed algorithm is verified via a simplified engine assembly case.