Multiple-Objective Particle Swarm Optimization for Multi-Head Beam-Type Surface Mounting Machines

The growing demand for electronic devices has made the manufacturing of printed circuit boards (PCBs) a promising industry over the last decades. As the demand for printed circuit boards increases, the industry becomes more dependent on highly automated assembly processes using Surface Mounting Devices (SMD). In this paper, after describing the overall optimization problem of assemblying a PCB type using a multi-head beam-type placement machine, this problem is decomposed into its sub-problems via a heirarchical approach. Then we formulate an integrated multi-objective mixed-integer nonlinear programming model considering the two main subproblems relating to the heads of the machine. Solving this nonlinear model directly is too complex and intractable. Therefore, the model is first linearized and then a multi-objective particle swarm optimization (MOPSO) algorithm is developed to solve it. The parameters of the proposed MOPSO algorithm are tuned based on the Taguchi Method and the corresponding numerical results are provided.