Machine Vision-Aided Quality Decision System for Solder Joint Defect Evaluation

Chien-Chih Wang ()
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Chien-Chih Wang: Ming Chi University of Technology

Chapter Chapter 14 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 147-157 from Springer

Abstract: Abstract To improve the printed circuit board (PCB) manufacturing process, it is important to have an automatic inspection system that classifies information regarding defects in solder joints. This paper proposes a quality decision system for solder joint defect classification on a PCB. An experiment was conducted to demonstrate the application of this technique. The results showed that the inspection accuracy reached 94%, which is superior to the results achieved by other methods. The results of this study provide an effective solution for the inspection of the solder joint quality.

Keywords: Automatic visual inspection; Multivariate analysis; Defect classification (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-37270-4_14

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DOI: 10.1007/978-3-642-37270-4_14

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