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데이터 마이닝 기법을 이용한 제조 공정내의 불량항목별 예측방법

Defect Type Prediction Method in Manufacturing Process Using Data Mining Technique

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참고문헌

주제분류산업공학

초록

Abstract

Data mining technique is the exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. This paper uses a data mining technique for the prediction of defect types in manufacturing process. The purpose of this paper is to model the recognition of defect type patterns and prediction of each defect type before it occurs in manufacturing process. The proposed model consists of data handling, defect type analysis, and defect type prediction stages. The performance measurement shows that it is higher in prediction accuracy than logistic regression model.

참고문헌 (9)

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  2. 최국렬 외 9명, "데이터마이닝 이론과 실습" (2001), 청구문화사
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  4. Douglas C.Montgomery, "Introduction to statistical quality control" (1996)
  5. Feng Yu Lin, "A data mining approach to the prediction of corporate failure"", 14. (2001)
  6. Michael J.A.Berry, "Data Mining Techniques" (1997)
  7. Y.C. Hsieh, "A neural network based model for abnormal pattern recognition of control charts", 36, pp.97~108 (1999)
  8. Velasco T, "Rowe MR. Back propagation artificial neural networks for the analysis of quality control charts.", pp.397~400 (1993)
  9. W.M.Hancock, "Use of Ridge Regression in the Improved Control of Casting Process", 8(3), pp.395~403 (1998)

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