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Proceedings Paper

Vision-based process control in layered manufacturing
Author(s): Yuan Cheng; Mohsen Jafari
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Paper Abstract

This paper combines defect detection and process control strategy into an efficient vision-based process control system in layered manufacturing. The purpose of our surface inspection, other than monitoring and classification of defects, is to improve the manufacturing process to reduce defects in subsequent stages. We examine the surface pattern using intensity image combined with CAD information. A hybrid strategy is used for defect analysis, where randomly occurred defects are detected by 2D texture analysis and assignable defects are obtained from 3D shape reconstruction using shape-from-shading. Instead of reconstructing the whole 3D surface, our approach reconstructs profile from representative signature(s) using parametric approach. In vision-based process control, we take defect information as input and determine the appropriate control parameter of current stage to minimize the possible defects. A linear model is developed and discussed.

Paper Details

Date Published: 1 May 2003
PDF: 11 pages
Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); doi: 10.1117/12.515076
Show Author Affiliations
Yuan Cheng, Rutgers Univ. (United States)
Mohsen Jafari, Rutgers Univ. (United States)


Published in SPIE Proceedings Vol. 5132:
Sixth International Conference on Quality Control by Artificial Vision

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