The Development of Automated Solder Bump Inspection using Machine Vision Techniques
Visual inspection is an important task in the manufacturing processes for integrated circuit boards. In this paper, we focus on the solder bump inspection problem, and an automated visual inspection method using machine vision techniques is proposed. The solder bump inspection method consists of image grabbing, image preprocessing, feature extraction, and defect detection and classification. Five defect types of solder bumps to be inspected are bridging solder, excess solder, incomplete solder, non-wetting, and missing solder. The solder area, the number of edge pixels, the deviation from center, and the deformation ratio are used as the features for solder bump defect detection and classification. The proposed method is a hybrid algorithm, and it consists of two stages: the training stage and the inspection stage. The experimental results show that the proposed method is effective in detecting defects of solder bumps.
Wu, W., Hung, C., & Yu, V. W. (2013). The Development of Automated Solder Bump Inspection using Machine Vision Techniques. International Journal of Advanced Manufacturing Technology, 69(1-4), pp. 509-523. Springer Verlag.
The definitive version is available at https://doi.org/10.1007/s00170-013-4994-x
Business and Information Technology
Keywords and Phrases
Automated visual inspection; Deformation ratio; Detecting defects; Hybrid algorithms; Image preprocessing; Inspection methods; Manufacturing process; Solder Bump; Computer vision; Defects; Feature extraction; Inspection; Soldering; Inspection; Machine vision
International Standard Serial Number (ISSN)
Article - Journal
© 2013 Springer Verlag, All rights reserved.
01 Oct 2013