다중회귀분석을 이용한 이상원인변수의 탐지에 관한 연구

• 영문명: A Study on the detection of the Fault Variable using Multiple Regression Analysis
• 발행기관: 한국산업경영시스템학회
• 저자명: 김용준(Yong-Jun Kim) 정영배(Young-Bae Chung)
• 간행물 정보: 『한국산업경영시스템학회 학술대회』2014년 춘계학술대회 논문집, 125~129쪽, 전체 4쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2014.05.10

영문 초록

Multivariate control charts are widely needed to monitor the production processes in various industry. Among the several multivariate control charts, control chart have been used of the typical technique. The control chart shows a statistic that represents observed variables and monitors the process through the statistic. In this case, the statistic generally have the limit that any variables affect to that statistic. To solve this problem, some studies have been progressed in the meantime. The representative method is to disassemble total statistic into each of the variable value and make a decision the parameters with large values than threshold value as a main cause. However, the means is requested to follow the normal distribution. To settle this problem, the bootstrap technique that don't be needed the probability distribution was introduced in 2011. In this paper, I introduced the detection technique of the fault variables using multiple regression analysis. There are two advantages; First, it is possible to use less samples than the ascertainment technique applying to bootstrap. Second, the technique using the regression analysis is easy to apply to the actual environment because the global threshold value is used.

목차

Abstract

1. 서론

2. Hotelling's T² 관리도와 분해기법

3. 다중 회귀분석에 기반한 T² 분해기법

4. 시뮬레이션

5. 결론

Reference

키워드

Multivariate control chart Regression analysis T² control chart