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Stream/Area:
-
Subject:
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Paper ID:
IJSREM65951
Volume:
10 |
7 |
Jul 2026
Pages:
1-3
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Mechanical Engineering
Chha shahu Engineering College Shambhajinagar
HOD ,Mechanical Engineering
Chha shahu Engineering College Shambhajinagar
Asst Professor , Mechanical Engineering
Chha shahu Engineering College Shambhajinagar
This paper presents an automated framework for the precision dimensional and tolerance evaluation of mechanical components using digital image acquisition and geometric comparison techniques. Traditional metrology tools, such as Coordinate Measuring Machines (CMMs) and manual calipers, are often limited by slow inspection speeds and contact-induced errors. To address these limitations, this study utilizes high-resolution industrial cameras and optimized illumination setups to capture precise two-digital images of manufactured components. Advanced edge-detection algorithms and sub-pixel extraction methods are applied to define the exact boundaries of the fabricated parts. These extracted geometric features are then structurally compared against a reference Computer-Aided Design (CAD) model or a nominal golden template. Geometric Dimensioning and Tolerance (GD&T) parameters—including flatness, circularity, parallelism, and concentricity—are calculated dynamically through spatial transformation and point-cloud alignment algorithms. Experimental results demonstrate that the proposed non-contact vision system achieves micron-level measurement accuracy, drastically reduces inspection cycle times, and provides an efficient, scalable solution for real-time quality control in high-precision manufacturing environments.
KEYWORDS
The proposed "Image Acquisition and Geometric Comparison of Mechanical Components for Precision Dimension and Tolerance Evaluation" system provides an efficient, accurate, and automated solution for dimensional inspection in manufacturing industries. By combining machine vision, image processing, and tolerance analysis techniques, the system minimizes manual inspection efforts and enhances quality assurance processes. The developed solution offers a low-cost alternative to conventional inspection systems while maintaining high levels of measurement accuracy and reliability. This project has significant potential for industrial implementation and future enhancement through AI, IoT, and advanced machine vision technologies.
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Publication Date
7/10/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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