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International Journal of Science, Strategic Management and Technology

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REVIEW ON LOW-COST IMAGE PROCESSING SOLUTION FOR RIVET QUALITY INSPECTION

AUTHORS:
Ojas Sonar
Pranav Bagul
Ruchita Taskar
Vaibhavi Thakare
Arun Zalte
Madhuri Malode
Mentor
Affiliation
Department, KBTCOE, Nashik, India  Founder and CEO, Ms Automations and Engineering, Nashik, India
DOI: 10.55041/ijsmt.v2i4.553
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

Rivets are critical fastening elements used in aerospace, automotive, and construction industries where structural integrity is essential. Traditional inspection methods rely on manual techniques, which are slow, inconsistent, and prone to human error. This paper presents a low-cost automated rivet inspection system using image processing and computer vision techniques. The proposed system integrates Python-based image processing, Programmable Logic Controllers (PLC), and Internet of Things (IoT) technologies to enable real-time inspection and monitoring. The system improves inspection accuracy, reduces processing time, and provides an affordable solution for small and medium-scale industries.

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Article Information
PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 04
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Apr 29 2026
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Sonar, O., Bagul, P., Taskar, R., Thakare, V., Zalte, A. & Malode, M. (2026). Review on Low-Cost Image Processing Solution for Rivet Quality Inspection. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.553

Sonar, Ojas, et al.. "Review on Low-Cost Image Processing Solution for Rivet Quality Inspection." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.553.

Sonar, Ojas,Pranav Bagul,Ruchita Taskar,Vaibhavi Thakare,Arun Zalte, and Madhuri Malode. "Review on Low-Cost Image Processing Solution for Rivet Quality Inspection." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.553.

References
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[2] M. Aslam, T. M. Khan, S. S. Naqvi, G. Holmes, and R. Naffa, "On the application of automated machine vision for leather defect inspection and grading: A survey," IEEE Access, vol. 7, pp. 176065–176086, 2019.

[3] J. Bai et al., "A comprehensive survey on machine learning driven material defect detection," ACM Comput. Surv., vol. 57, pp. 1–36, 2025.

[4] F. Kashefinishaburi and S. V. Hoa, "A technique for real-time defect detection of composite material using machine learning and transfer learning," in Proc. American Society for Composites, 2022.

[5] M. Hussain, "Sustainable machine vision for Industry 4.0: A review of CNNs and hardware accelerators," AI, vol. 5, pp. 1324–1356, 2024.

[6] A. Sioma, "Vision system in product quality control systems," Appl. Sci., vol. 13, p. 751, 2023.

[7] M. Dziubek et al., "Exploring the ViDiDetect tool for automated defect detection," Appl. Sci., vol. 13, p. 11098, 2023.

[8] IEC 61131-3, "Programmable Controllers—Part 3: Programming Languages," 2013.

[9] D. Jancarczyk et al., "Comparative analysis of measurement tools in the Cognex D900 vision system," Appl. Sci., vol. 14, p. 8296, 2024.

[10] B. Kim, M. Shin, and S. Hwang, "Precision defect detection using line scan camera and deep learning," Appl. Sci., vol. 14, p. 12054, 2024.
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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