Proceedings of the 8th International Conference on Applied Engineering (ICAE 2025)

<Previous Article In Volume
Next Article In Volume>

Semi-Automatic Tilt Detection on PCBA Against Front Cap

Authors
Abdullah Sani1, *, Lusia Puspita Kusumadewi2
1Batam State Polytechnic, Batam, Indonesia
2Batam State Polytechnic, Batam, Indonesia
*Corresponding author. Email: sani@polibatam.ac.id
Corresponding Author
Abdullah Sani
Available Online 29 December 2025.
DOI
10.2991/978-94-6463-982-7_8How to use a DOI?
Keywords
Convolutional Neural Network; Image Classification; Printed Circuit Board
Abstract

A prevalent issue in electronics manufacturing is that of positional misalignment of the Printed Circuit Board Assembly (PCBA) with the product's front cap. This issue has been shown to result in product defects and material waste. To address these issues, the research proposes a semi-automatic tilt detection system based on a Convolutional Neural Network (CNN). The system has been engineered to inspect the alignment of an electret microphone component by capturing real-time images with a webcam, subjecting the da-ta to preprocessing, and then classifying position using a trained CNN model. The model categorizes the PCBA position into four classes: normal, gap, tilted right, and tilted left. Real-time testing demonstrated an average accuracy of 88.4%, with the “Normal” class achieving a perfect precision of 100%. This system offers an effective solution to enhance quality control and reduce human error in electronic assembly lines.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 8th International Conference on Applied Engineering (ICAE 2025)
Series
Advances in Engineering Research
Publication Date
29 December 2025
ISBN
978-94-6463-982-7
ISSN
2352-5401
DOI
10.2991/978-94-6463-982-7_8How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Abdullah Sani
AU  - Lusia Puspita Kusumadewi
PY  - 2025
DA  - 2025/12/29
TI  - Semi-Automatic Tilt Detection on PCBA Against Front Cap
BT  - Proceedings of the  8th International Conference on Applied Engineering (ICAE 2025)
PB  - Atlantis Press
SP  - 113
EP  - 131
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-982-7_8
DO  - 10.2991/978-94-6463-982-7_8
ID  - Sani2025
ER  -