Optimizing the Operation Sequence of  
                        a Multihead Surface Mounting Machine Using  
                        a Discrete Particle Swarm Optimization Algorithm

Chen, Yee Ming; Lin, Chun-Ta

doi:https://doi.org/10.1155/2008/315950

Journal of Artificial Evolution and Applications

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Particle Swarms: The Second Decade

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Research Article | Open Access

Volume 2008 | Article ID 315950 | https://doi.org/10.1155/2008/315950

Optimizing the Operation Sequence of a Multihead Surface Mounting Machine Using a Discrete Particle Swarm Optimization Algorithm

Yee Ming Chen¹and Chun-Ta Lin²

Academic Editor: Riccardo Poli

Received19 Jul 2007

Revised12 Feb 2008

Accepted25 Mar 2008

Published29 Apr 2008

Abstract

The optimization of the nozzle selection, for sequencing component pick and place operations, is very important to the efficiency of multihead surface mounting machine (SMM). The nozzle change operation, that is, choosing the best nozzle head relative pair that is most effective for picking and placing components onto the printed circuit board (PCB), significantly adds to the overall assembly time. In this paper, as a practical application, we focus on a discrete particle swarm optimization (DPSO) algorithm for multihead SMM which is used to minimize the number of nozzle change operations and pick and place operations simultaneously. To evaluate the performance of the proposed algorithm, we test it on assembly tasks of PCBs through simulations. The results of computer experiments show that this DPSO algorithm was superior to the standard PSO algorithm.

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Copyright

Copyright © 2008 Yee Ming Chen and Chun-Ta Lin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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