DocumentCode :
2631238
Title :
Defect diagnosis of solder joints using fuzzy logic
Author :
Heikkinen, Jouko ; Klapuri, Hani ; Saarinen, Jukka ; Oksanen, Hannu ; Kastepohja, Ari ; Urpelainen, Markku
Author_Institution :
Electron. Lab., Tampere Univ. of Technol., Finland
fYear :
1996
fDate :
4-6 Sep 1996
Firstpage :
502
Lastpage :
509
Abstract :
This paper describes how the methods of fuzzy logic can be used in the classification of solder joint inspection results. The inspection results of over 900 circuit boards have been analysed for the purpose of distinguishing the essential characters of defective and decent solder joints. Also the effect of the prevailing average solder amount of each component type on the decision making process has been considered. The developed prototype of a fuzzy classifier of defect reports accomplishes the classification by using the information received from the solder joint inspection system. Defect reports are classified to be either justified or unnecessary. The classifier is able to detect about 80% of unnecessary defect reports and thus reduces the amount of work in the required visual re-inspection
Keywords :
printed circuit manufacture; PCB manufacture; decision making process; defect diagnosis; fuzzy classifier; fuzzy logic; fuzzy set theory; knowledge based systems; pattern classification; solder joint inspection; tomography; Decision making; Fuzzy logic; Fuzzy systems; Inspection; Printed circuits; Prototypes; Signal processing; Soldering; Tin; Tomography;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing [1996] VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop
Conference_Location :
Kyoto
ISSN :
1089-3555
Print_ISBN :
0-7803-3550-3
Type :
conf
DOI :
10.1109/NNSP.1996.548380
Filename :
548380
Link To Document :
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