KIPS Transactions on Software and Data Engineering (정보처리학회논문지:소프트웨어 및 데이터공학)

Korea Information Processing Society (한국정보처리학회)
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Fault-Causing Process and Equipment Analysis of PCB Manufacturing Lines Using Data Mining Techniques

데이터마이닝 기법을 이용한 PCB 제조라인의 불량 혐의 공정 및 설비 분석

  • 심현식 (연세대학교 정경대학) ;
  • 김창욱 (연세대학교 정보산업공학과)
  • Received : 2014.05.28
  • Accepted : 2014.09.25
  • Published : 2015.02.28
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Abstract

In the PCB(Printed Circuit Board) manufacturing industry, the yield is an important management factor because it affects the product cost and quality significantly. In real situation, it is very hard to ensure a high yield in a manufacturing shop because products called chips are made through hundreds of nano-scale manufacturing processes. Therefore, in order to improve the yield, it is necessary to analyze main fault process and equipment that cause low PCB yield. This paper proposes a systematic approach to discover fault-causing processes and equipment by using a logistic regression and a stepwise variable selection procedure. We tested our approach with lot trace records of real work-site. A lot trace record consists of the equipment sequence that the lot passed through and the number of faults for each fault type in the lot. We demonstrated that the test results reflected the real situation of a PCB manufacturing line.

PCB(Printed Circuit Board) 제조공정에서의 수율은 제품의 원가와 품질을 결정하는 중요한 관리 요인이다. PCB 제조공정은 일반적으로 많은 단계의 미세공정을 거쳐서 제품인 칩(Chip)이 생산되기 때문에 높은 수율을 보장하기가 현실적으로 어렵다. 제품의 수율을 향상시키기 위해서는 저수율의 원인이 되는 불량요인을 분석하고, 불량요인에 영향을 미치는 중요공정 및 설비를 찾아서 관리해야 한다. 본 연구는 로지스틱 회귀분석 및 변수선택법을 이용하여 혐의공정 및 설비를 찾는 방법을 제안하였다. 데이터는 실제 현장의 로트 데이터를 사용하였고, 각 로트는 진행한 설비 및 불량유형별 불량수를 갖고 있다. 또한 분석 결과는 실제 현장 확인을 통하여 수율에 미치는 영향을 확인하였다.

Keywords

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