This paper uses a data mining methodologies to improve and predict cause of defect process variables in manufacturing process. Traditional statistical process control (SPC) techniques of control charting are not applicable in many process industries because it is difficult to analyze the cause of many process variables. The paper suggests that data mining methodologies useful when sequence rule, SVM (classification) methods are find out cause of defect process variables and SVM (prediction) methods used to predict process variables in manufacturing process. Therefore, it is allowing improved control in manufacturing process.

Abstract
 1. 서론
 2. 공정변수 파악 및 개선방법
  2.1 공정 모니터링
  2.2 공정변수 파악
  2.3 공정 분류
  2.4 공정변수 패턴파악
  2.5 공정변수 값 예측
  2.6 공정개선 및 적용
 3. 사례연구
  3.1 공정소개
  3.1 공정 모니터링
  3.3 공정변수 파악
  3.4 공정분류
  3.5 공정변수 패턴파악
  3.6 공정변수 값 예측
  3.7 공정개선 및 적용
  3.8 사례분석 및 토의
 4. 결론
 참고문헌

• 정영수(한양대학교 산업공학과)
• 강창욱(한양대학교 정보경영공학과)