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Intelligent parametric design for a multiple-quality-characteristic glue-dispensing process

Author

Listed:
  • Chien-Yi Huang

    (National Taipei University of Technology)

  • Kuo-Ching Ying

    (National Taipei University of Technology)

Abstract

For double-sided circuit boards, a wave soldering carrier is generally used to shield the devices mounted on the surface of the first side of the printed circuit board (PCB), so that the solder joints are not melted again through exposure to tin wave, causing the devices to deviate or fall as a result of flushing. However, carrier adoption increases production costs. This study proposes a glue-dispensing process to replace the wave soldering carrier. In addition, glue curing and reflow soldering were performed simultaneously to enhance production efficiency. An ecofriendly glue-dispensing process using low-cost CEM-1 substrates and a glue materials featuring a low curing temperature helps reduce energy consumption and carbon emissions. The Taguchi method was used to plan and execute this experiment. The quality characteristics of assembly reliability and manufacturing costs were considered in terms of glue thrust strength and per-PCB manufacturing cost, respectively. An intelligent parametric design applying PCA statistical methods and artificial neural networks (ANN) model was proposed. Results of a confirmation test indicated that the optimal parameter combination suggested by the ANN model was superior. The most satisfactory procedure parameter combination obtained comprised GMIR-130HF for the glue material, a curing temperature of $$140\,^{\circ }\hbox {C}$$ 140 ∘ C , a 1.1 m/min conveyor velocity, and a 0.09 Mpa dispensing pressure.

Suggested Citation

  • Chien-Yi Huang & Kuo-Ching Ying, 2019. "Intelligent parametric design for a multiple-quality-characteristic glue-dispensing process," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2291-2305, June.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:5:d:10.1007_s10845-017-1389-0
    DOI: 10.1007/s10845-017-1389-0
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    References listed on IDEAS

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    1. Xueping Li & Nong Ye & Xiaoyun Xu & Rapinder Sawhey, 2007. "Influencing factors of job waiting time variance on a single machine," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 1(1), pages 56-73.
    2. Abbas Al-Refaie & Wafa’a Al-Alaween & Ali Diabat & Ming-Hsien Li, 2017. "Solving dynamic systems with multi-responses by integrating desirability function and data envelopment analysis," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 387-403, February.
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    Cited by:

    1. Ahmed Ktari & Mohamed El Mansori, 2022. "Digital twin of functional gating system in 3D printed molds for sand casting using a neural network," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 897-909, March.

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