Estimation of the PCB Production Process Using a Neural Network

  • Kuo-Hsien Hsia Department of Computer Science and Information Engineering, Far East University, Tainan, Taiwan
  • Jr-Hung Guo Department of Electrical Engineering, National Yunlin University of Science & Technology, Yunlin, Taiwan
Keywords: printed circuit board (PCB), neural network, Gerber file, production schedule

Abstract

Printed Circuit Boards (PCB) are an integral part of all electronic products, and the production process for printed circuit boards is quite complex. As the life cycle of electronic products becomes shorter and shorter, and the precision and signal bandwidth of electronic products become higher and higher, the manufacturing process of printed circuit boards is further complicated. Therefore, how to pre-evaluate the production difficulty before starting the production will effectively increase the efficiency and quality of printed circuit board production.

Gerber file is the most commonly used data format for the printed circuit board industry. This file contains most of the parameters required for the manufacture of printed circuit boards. Therefore, this study uses a neural network to evaluate new PCB products before they are produced through the production parameters that are more influential in the PCB manufacturing process. This makes it possible to evaluate the difficulty and the required production process before the new PCB product is produced. This will be very beneficial for the PCB production schedule, quality control, and cost.

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Published
2020-04-27
How to Cite
Hsia, K.-H., & Guo, J.-H. (2020). Estimation of the PCB Production Process Using a Neural Network. Proceedings of Engineering and Technology Innovation, 15, 01-07. Retrieved from http://ojs.imeti.org/index.php/PETI/article/view/4265
Section
Articles