지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학위논문
- 저자정보
- 지도교수
- 金性範
- 발행연도
- 2016
- 저작권
- 고려대학교 논문은 저작권에 의해 보호받습니다.
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이 논문의 연구 히스토리 (5)
2016
- 이 논문의 후속연구가 궁금하신가요?
- 연관 학술논문 또는 학술발표를 통해 보다 발전된 연구결과를 확인하실 수 있습니다.
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초록· 키워드
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Prediction of field failure rates plays an important role for establishing appropriate management policies and improving the profitability for industries. For these reasons, many LCD (Liquid crystal display) manufacturing industries have attempted to construct prediction models for field failure rates. However, most traditional models are based on the parametric approaches requiring the assumption that the data follow a certain probability distribution. To address the limitation posed by the distributional assumption underpinning traditional models, we propose using parameter-free data mining models for predicting field failure rates. In addition, we use various information associated with product attributes and field return for more comprehensive analysis. The effectiveness and applicability of the proposed method were demonstrated with a real dataset from one of the leading LCD companies in South Korea.
목차
ABSTRACT ···················································································· ⅠCONTENTS ··················································································· ⅡCHAPTER 1. 서론 ·········································································· 1CHAPTER 2. 데이터마이닝 기반 시장 불량률 예측 ··············· 11CHAPTER 3. 실험 계획 및 결과 ················································ 22CHAPTER 4. 결론 ········································································ 31REFERENCE ················································································ 34
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