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Optimizing the Operation Sequence of a Multihead Surface Mounting Machine Using a Discrete Particle Swarm Optimization Algorithm
Author(s) -
Yee Ming Chen,
Chun-Ta Lin
Publication year - 2008
Publication title -
journal of artificial evolution and applications
Language(s) - English
Resource type - Journals
eISSN - 1687-6237
pISSN - 1687-6229
DOI - 10.1155/2008/315950
Subject(s) - computer science , nozzle , particle swarm optimization , algorithm , component (thermodynamics) , focus (optics) , selection (genetic algorithm) , sequence (biology) , swarm behaviour , smt placement equipment , artificial intelligence , engineering , mechanical engineering , physics , genetics , optics , biology , robot , thermodynamics
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 tominimize 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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