Detection and Isolation of Wheelset Intermittent Over-Creeps for Electric Multiple Units Based on a Weighted Moving Average Technique

When the production run is short and process parameters change frequently, it is difficult to monitor the process using traditional control charts. In such a case, the coefficient of variation (CV) is very useful for monitoring the process variability. The CV control chart, however, is not sensitive at small shift in the magnitude of CV. The CV-EWMA (exponentially weighted moving average) control chart which was developed recently is effective in detecting a small shifts of CV. In this paper, we propose the CV-DEWMA control chart, combining the DEWMA (double exponentially weighted moving average) technique. We show that CV-DEWMA control chart perform better than CV-EWMA control chart in detecting small shifts when sample size n is larger than 5.

Download Full-text

Fuzzy thresholding: mathematical framework, bound functions and weighted moving average technique

Pattern Recognition Letters ◽

10.1016/0167-8655(90)90006-n ◽

1990 ◽

Vol 11 (3) ◽

pp. 197-206 ◽

Cited By ~ 56

Author(s):

Chivukula A. Murthy ◽

Sankar K. Pal

Keyword(s):

Moving Average ◽

Mathematical Framework ◽

Average Technique ◽

Fuzzy Thresholding ◽

Weighted Moving Average

Download Full-text

Demerit-GWMA Control Chart for Demerit Statistics

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.156-157.413 ◽

2010 ◽

Vol 156-157 ◽

pp. 413-421

Author(s):

Hae Woon Kang ◽

Chang Wook Kang ◽

Jae Won Baik ◽

Sung Ho Nam

Keyword(s):

Control Chart ◽

Mobile Phones ◽

Moving Average ◽

Exponentially Weighted Moving Average ◽

Process Mean ◽

Average Technique ◽

Complex Products ◽

Ewma Control Chart ◽

Weighted Moving Average ◽

Exponentially Weighted

A classical Demerit control chart is used to monitor the process through which various types of defects in complex products, such as automobiles, computers, mobile phones, etc. are found in general. As a technique for rapidly detecting small shifts of the process mean in the control chart, the EWMA(exponentially weighted moving average) technique is very effective. This study suggested the Demerit-GWMA control chart, combining the GWMA(generally weighted moving average) technique, which shows better performance than EWMA technique in detecting small shifts of process mean, into the classical Demerit control chart, and evaluated its performance. Through the evaluation of its performance, it was found that the Demerit-GWMA control chart is more sensitive than both the classical Demerit control chart and the Demerit-EWMA control chart in detecting small shifts of process mean.

Download Full-text

CV Control Chart Using GWMA Technique

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.337.247 ◽

2011 ◽

Vol 337 ◽

pp. 247-254 ◽

Cited By ~ 4

Author(s):

Eui Pyo Hong ◽

Hae Woon Kang ◽

Chang Wook Kang ◽

Jae Won Baik

Keyword(s):

Control Chart ◽

Control Charts ◽

Moving Average ◽

Exponentially Weighted Moving Average ◽

Average Technique ◽

Ewma Control Chart ◽

Production Run ◽

Average Control ◽

Weighted Moving Average ◽

Exponentially Weighted

When the production run is short and process parameters change frequently, it is difficult to monitor the process using traditional control charts. In such a case, the coefficient of variation (CV) is very useful for monitoring the process variability. The CV control chart, however, is not sensitive at small shifts in the magnitude of CV. This study suggest the CV-GWMA(generally weighted moving average) control chart, combining the GWMA technique, which shows better performance than the EWMA(exponentially weighted moving average) or DEWMA(double exponentially weighted moving average) technique in detecting small shifts of the process. Through a performance evaluation, the proposed control chart showed more excellent performance than the existing CV-EWMA control chart or the CV-DEWMA control chart in detecting small shifts in CV.

Download Full-text