Image processing framework for in-process shaft diameter measurement on legacy manual machines

In-process dimension measurement is critical to achieving higher productivity and realizing smart manufacturing goals during machining operations. Vision-based systems have significant potential to serve for in-process dimensions measurements, reduce human interventions, and achieve manufacturing-in...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology 2024-12, Vol.135 (9-10), p.4323-4338
Main Authors: Choudhari, Sahil J., Singh, Swarit Anand, Kumar, Aitha Sudheer, Desai, Kaushal A.
Format: Article
Language:English
Subjects:
Advanced manufacturing technologies
Algorithms
Automation
CAE) and Design
Computer-Aided Engineering (CAD
Diameters
Digitization
Engineering
Image acquisition
Image processing
Image segmentation
Industrial and Production Engineering
Machining
Manufacturing
Mechanical Engineering
Media Management
Object recognition
Original Article
Pixels
Productivity
Real time
Vision systems
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Summary:In-process dimension measurement is critical to achieving higher productivity and realizing smart manufacturing goals during machining operations. Vision-based systems have significant potential to serve for in-process dimensions measurements, reduce human interventions, and achieve manufacturing-inspection integration. This paper presents early research on developing a vision-based system for in-process dimension measurement of machined cylindrical components utilizing image-processing techniques. The challenges with in-process dimension measurement are addressed by combining a deep learning-based object detection model, You Only Look Once version 2 (YOLOv2), and image processing algorithms for object localization, segmentation, and spatial pixel estimation. An automated image pixel calibration approach is incorporated to improve algorithm robustness. The image acquisition hardware and the real-time image processing framework are integrated to demonstrate the working of the proposed system by considering a case study of in-process stepped shaft diameter measurement. The system implementation on a manual lathe demonstrated robust utilities, eliminating the need for manual intermittent measurements, digitized in-process component dimensions, and improved machining productivity.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-024-14750-x