손실 비용을 고려한 공정 파라미터 허용차 산출 :

• 영문명: Tolerance Computation for Process Parameter Considering Loss Cost :
• 발행기관: 한국산업경영시스템학회
• 저자명: 김용준(Yong Jun Kim) 김근식(Geun Sik Kim) 박형근(Hyung Geun Park)
• 간행물 정보: 『산업경영시스템학회지』제40권 제2호, 129~136쪽, 전체 8쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2017.06.30

영문 초록

Among the information technology and automation that have rapidly developed in the manufacturing industries recently, tens of thousands of quality variables are estimated and categorized in database every day. The former existing statistical methods, or variable selection and interpretation by experts, place limits on proper judgment. Accordingly, various data mining methods, including decision tree analysis, have been developed in recent years. Cart and C5.0 are representative algorithms for decision tree analysis, but these algorithms have limits in defining the tolerance of continuous explanatory variables. Also, target variables are restricted by the information that indicates only the quality of the products like the rate of defective products. Therefore it is essential to develop an algorithm that improves upon Cart and C5.0 and allows access to new quality information such as loss cost. In this study, a new algorithm was developed not only to find the major variables which minimize the target variable, loss cost, but also to overcome the limits of Cart and C5.0. The new algorithm is one that defines tolerance of variables systematically by adopting 3 categories of the continuous explanatory variables. The characteristics of larger-the-better was presumed in the environment of programming R to compare the performance among the new algorithm and existing ones, and 10 simulations were performed with 1,000 data sets for each variable. The performance of the new algorithm was verified through a mean test of loss cost. As a result of the verification show, the new algorithm found that the tolerance of continuous explanatory variables lowered loss cost more than existing ones in the larger is better characteristics. In a conclusion, the new algorithm could be used to find the tolerance of continuous explanatory variables to minimize the loss in the process taking into account the loss cost of the products.

목차

1. 서 론

2. 이론적 배경

3. 연구 설계

4. 시뮬레이션

5. 결 론

References

키워드

Continuous Variable Decision Tree Larger-is-Better Characteristics Loss Cost Tolerance