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Using an Improved Differential Evolution for Scheduling Optimization of Dual-Gantry Multi-Head Surface-Mount Placement Machine

Author

Listed:
  • Cheng-Jian Lin

    (Department of Computer Science & Information Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
    College of Intelligence, National Taichung University of Science and Technology, Taichung 404, Taiwan)

  • Chun-Hui Lin

    (Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan)

Abstract

The difference between dual-gantry and single-gantry surface-mount placement (SMP) machines is that dual-gantry machines exhibit higher complexity and more problems due to their additional gantry robot, such as component allocation and collision. This paper presents algorithms to prescribe the assembly operations of a dual-gantry multi-head surface-mount placement machine. It considers five inter-related problems: (i) component allocation; (ii) automatic nozzle changer assignment; (iii) feeder arrangement; and (iv) pick-and-place sequence; it incorporates a practical restriction related to (v) component height. The paper proposes a solution to each problem: (i) equalizing “workloads” assigned to the gantries, (ii) using quantity ratio method, (iii) using two similarity measurement mechanisms in a modified differential evolution algorithm with a random-key encoding mapping method that addresses component height restriction, (iv) and a combination of nearest-neighbor search and 2-opt method to plan each placing operation. This study reports an experiment that involved the processing of 10 printed circuit boards and compared the performance of a modified differential evolution algorithm with well-known algorithms including differential evolution, particle swarm optimization, and genetic algorithm. The results reveal that the number of picks, moving distance of picking components, and total assembly time with the modified differential evolution algorithm are less than other algorithms.

Suggested Citation

  • Cheng-Jian Lin & Chun-Hui Lin, 2021. "Using an Improved Differential Evolution for Scheduling Optimization of Dual-Gantry Multi-Head Surface-Mount Placement Machine," Mathematics, MDPI, vol. 9(16), pages 1-22, August.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:16:p:2016-:d:620260
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    References listed on IDEAS

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    1. Ashayeri, J. & Ma, N. & Sotirov, R., 2010. "An Aggregated Optimization Model for Multi-Head SMD Placements," Other publications TiSEM 9947d4db-ac1f-46e0-9616-c, Tilburg University, School of Economics and Management.
    2. H. Faria & M. G. C. Resende & D. Ernst, 2017. "A biased random key genetic algorithm applied to the electric distribution network reconfiguration problem," Journal of Heuristics, Springer, vol. 23(6), pages 533-550, December.
    3. Ashayeri, J. & Ma, N. & Sotirov, R., 2010. "An Aggregated Optimization Model for Multi-Head SMD Placements," Other publications TiSEM 9947d4db-ac1f-46e0-9616-c, Tilburg University, School of Economics and Management.
    4. James C. Bean, 1994. "Genetic Algorithms and Random Keys for Sequencing and Optimization," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 154-160, May.
    5. Sun, Dong-Seok & Lee, Tae-Eog & Kim, Kyung-Hoon, 2005. "Component allocation and feeder arrangement for a dual-gantry multi-head surface mounting placement tool," International Journal of Production Economics, Elsevier, vol. 95(2), pages 245-264, February.
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