• 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