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Related Experiment Video

Updated: Jan 11, 2026

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A fully automated drilling machine for printed circuit boards with superior path optimization.

Mohamed Mamdouh1, Ahmed Khalid1, Reem Mahmoud1

  • 1The Electrical Engineering Department and FabLab, Centre of Emerging Learning Technologies CELT, British University in Egypt (BUE), Cairo, 11387, Egypt.

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|November 18, 2025
PubMed
Summary

This study introduces an AI-powered automated drilling machine for Printed Circuit Board (PCB) manufacturing. It significantly reduces errors and production time through optimized drilling paths, improving efficiency and quality.

Keywords:
AI-driven automationG-Code generationKiCAD EDAPCB manufacturingPath planning

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Area of Science:

  • Engineering
  • Computer Science
  • Manufacturing Technology

Background:

  • Current Printed Circuit Board (PCB) manufacturing faces challenges with precision and time due to complex designs.
  • Existing drilling methods struggle with varying hole sizes, component placements, and intricate geometries.
  • This leads to compromised accuracy and extended production cycles in PCB fabrication.

Purpose of the Study:

  • To propose an AI-driven, fully automated drilling machine for enhanced PCB manufacturing.
  • To optimize drilling paths using advanced algorithms for improved precision and reduced production time.
  • To address limitations in current methodologies for assessing complex PCB designs.

Main Methods:

  • Development of an AI-driven automated drilling machine incorporating sophisticated path-planning algorithms.
  • Intelligent analysis of PCB designs to optimize drilling sequences and minimize errors.
  • Utilization of KiCAD EDA software for automated generation of Gerber files and G-Codes.

Main Results:

  • Achieved a 13-fold improvement in routing efficiency compared to manual methods.
  • Demonstrated significant reduction in production time and minimization of manufacturing errors.
  • Validated system effectiveness through successful continuity tests and superior quality finishes in PCB production.

Conclusions:

  • The AI-driven automated drilling system offers a substantial advancement in PCB manufacturing efficiency and precision.
  • This research paves the way for further integration of machine learning and optimization techniques in electronics design.
  • The proposed system enhances overall productivity and ensures high-quality circuit board production.