Vision-based process control in layered manufacturing

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.