• DocumentCode
    3518990
  • Title

    Component Placement Process Optimization for Multi-Head Surface Mounting Machine Based on Tabu Search and Improved Shuffled Frog-Leaping Algorithm

  • Author

    Chen, Tiemei ; Luo, Jiaxiang ; Hu, Yueming

  • Author_Institution
    Eng. Res. Center for Precision Electron. Manuf. Equipments of Minist. of Educ., South China Univ. of Technol., Guangzhou, China
  • fYear
    2011
  • fDate
    28-29 May 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper considers the SMT placement process optimization problem to minimize the assembly time of Multi-head surface mounting machine (SMM).A mathematical model is firstly established.Considering that the component pick-and-place sequencing and the feeder assignment are the two main important factors which determine the assembly time of a device,the optimization problem is divided into two sub-problems,called feeder assignment sub-problem and the component pick-place sequencing sub-problem.Then the tabu search algorithm and the improved shuffled frog leaping algorithm with mutation are applied to optimize the two sub-problems respectively.Finally,according to the thoughts of iteration and cooperation,the two interrelated sub-problems could be cooperated with each other to improve the efficiency of optimization.To verify the efficiency of the algorithm,experiments on 10 PCBs instances are executed.Experimental results show that the algorithm could obtain satisfied quasi-optimal solutions to the mounting process,and it makes an improvement 9.55% on the hybrid genetic algorithm reported in literature.
  • Keywords
    genetic algorithms; printed circuits; search problems; surface mount technology; PCB; SMT placement process optimization problem; component pick-place sequencing sub-problem; component placement process optimization; feeder assignment sub-problem; hybrid genetic algorithm; improved shuffled frog-leaping algorithm; multihead surface mounting machine; tabu search algorithm; Algorithm design and analysis; Genetic algorithms; Heuristic algorithms; Magnetic heads; Optimization; Resource management; Search problems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Applications (ISA), 2011 3rd International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9855-0
  • Electronic_ISBN
    978-1-4244-9857-4
  • Type

    conf

  • DOI
    10.1109/ISA.2011.5873252
  • Filename
    5873252