Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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Development of an Effective Defect Classification System for Inspection of QFN Semiconductor Packages

QFN 반도체 패키지의 외형 결함 검사를 위한 효과적인 결함 분류 시스템 개발

  • 김효준 (호서대학교 대학원 전자공학과) ;
  • 이정섭 (호서대학교 대학원 디지털 디스플레이공학과) ;
  • 주효남 (호서대학교 디스플레이공학과) ;
  • 김준식 (호서대학교 전자공학과)
  • Published : 2009.04.30
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Abstract

There are many different types of surface defects on semiconductor Integrated Chips (IC's) caused by various factors during manufacturing process, such as cracks, foreign materials, chip-outs, chips, and voids. These defects must be detected and classified by an inspection system for productivity improvement and effective process control. Among defects, in particular, foreign materials and chips are the most difficult ones to classify accurately. A vision system composed of a carefully designed optical system and a processing algorithm is proposed to detect and classify the defects on QFN(Quad Flat No-leads) packages. The processing algorithm uses features derived from the defect's position and brightness value in the Maximum Likelihood classifier and the optical system is designed to effectively extract the features used in the classifier. In experiments we confirm that this method gives more effective result in classifying foreign materials and chips.

반도체 외관결함에는 발생 요인이 각각 다른 crack, foreign material, chip-out, chip, void 등이 있으며, 검사 시스템에서는 결함 유무 및 결함 분류를 수행하여 효과적인 공정관리가 가능하여야 한다. 본 논문에서는 QFN 패키지 결함의 분류를 위한 알고리즘 및 광학시스템을 제안한다. 제안한 방법에서 분류가 어려운 결함 중 하나인 foreign material 과 chip의 효과적인 분류를 위해 제안한 결함의 위치, 밝기의 특징정보(feature)를 사용한 ML(Maximum Likelihood ratio) 분류방법 및 특징정보 획득에 효과적인 광학계를 제안하였다. 실험 결과에서 분류가 어려운 foreign material과 chip에 대한 신뢰성 높은 분류성능을 보였다.

Keywords

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