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Erschienen in:

2013 | OriginalPaper | Buchkapitel

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

verfasst von : Chien-Chih Wang

Erschienen in: The 19th International Conference on Industrial Engineering and Engineering Management

Verlag: Springer Berlin Heidelberg

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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.

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Vorheriges Kapitel Production Process Improvement Using the Six Sigma DMAIC Methodology: A Case Study of a Laser Computer Mouse Production Process

Nächstes Kapitel Demand Analysis and Framework of Theory About Chinese Events Sports Logistics

This research was supported by the National Science Council of Taiwan, Project Number NSC 90-2218-E-131-012 and NSC 91-2218-E-131-005.

Chu CC, Jiang BC, Wang CC (2008) Modified gamma correlation method to enhance BGA surface image for surface defect inspection. Int J Prod Res 46(8):2165–2178CrossRef

Jiang BC, Wang YM, Wang CC (2001) Bootstrap sampling techniques applied to PCB golden fingers defect classification study. Int J Prod Res 39(10):2215–2230CrossRef

Jiang BC, Tasi SL, Wang CC (2002) Machine-vision based grey relational theory applied to IC marking inspection. IEEE Trans Semicond Manuf 15(4):531–539CrossRef

Jiang BC, Wang CC, Chen PL (2004) Logistic regression tree applied to classify PCB golden finger defects. Int J Adv Manuf Technol 24(7):496–502CrossRef

Jiang BC, Wang CC, Hau YN (2007) Machine vision and background remover-based approach for PCB solder joints inspection. Int J Prod Res 45(2):451–464CrossRef

Jiang BC, Wang CC, Chen HJ, Chu CC (2010) Automatic bubble defect inspection for microwave communication substrates using multi-threshold technique based co-occurrence matrix. Int J Prod Res 48(8):2361–2371CrossRef

Ko KW, Cho HS (2000) Solder joints inspection using a neural network and fuzzy rule-based classification method. IEEE Trans Electron Pack Manuf 23(2):93–103CrossRef

Mardai KV (1970) Measures of multivariate skewness and kurtosis with applications. Biometrika 36:519–530CrossRef

Oyeleye OU, Lehtihet EA (1999) Automatic visual inspection of surface mount solder joint defects. Int J Prod Res 37:1217–1242CrossRef

Ripley BD (1996) Pattern recognition and neural networks. Cambridge University Press, New York

Smith SP, Jain AK (1988) A test to determine the multivariate normality of a dataset. IEEE Trans Pattern Anal Mach Intell 10:757–761CrossRef

Wang CC, Jiang BC (2001) PCB solder joints defects detection and classification using machine vision. Int J Ind Eng 8(4):359–368

Wang CC, Jiang BC, Chou YS, Chu CC (2011) Multivariate analysis techniques-based image enhancement model for electronic products inspection. Int J Prod Res 49(15):2999–3021CrossRef

Titel: Machine Vision-Aided Quality Decision System for Solder Joint Defect Evaluation
verfasst von: Chien-Chih Wang
Verlag: Springer Berlin Heidelberg
Buch: The 19th International Conference on Industrial Engineering and Engineering Management
Print ISBN: 978-3-642-37269-8

Electronic ISBN: 978-3-642-37270-4

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-3-642-37270-4_14