Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 7-Day Trial for You or Your Team.

Learn More →

The development and evaluation of CUSUM-based control charts for an AR(1) process

The development and evaluation of CUSUM-based control charts for an AR(1) process Abstract An important component of the quality program of many manufacturing operations is the use of control chart for variables. Inherent in the construction of these control charts is the assumption that the sampled process is a normal distribution whose observations are independent and identically distributed (iid). Many processes such as those found in chemical manufacturing, refinery operations, smelting operations, wood product manufacturing, waste-water processing and the operation of nuclear reactors have been shown to have autocorrelated observations. Autocorrelation, which violates the independence assumption of standard control charts, is known to have an adverse effect on the average run length (ARL) performance of control charts. This paper will consider a statistical testing procedure for the change-point problem for monitoring the level parameter of the AR(1) process. This test is shown to result in a CUSUM-based control chart. Two different solutions of the change-point problem are given which result in slightly different control charts. The average run length of each of these CUSUM control charts is found via the Markov chain approach. A methodology for designing the CUSUM-based control chart is presented and the performance of these control charts is compared to other approaches in the literature. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png IISE Transactions Taylor & Francis

The development and evaluation of CUSUM-based control charts for an AR(1) process

Download PDF
10 pages

Loading next page...
 
/lp/taylor-francis/the-development-and-evaluation-of-cusum-based-control-charts-for-an-ar-dAejTembw8

References (8)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1545-8830
eISSN
0740-817X
DOI
10.1080/07408179808966492
Publisher site
See Article on Publisher Site

Abstract

Abstract An important component of the quality program of many manufacturing operations is the use of control chart for variables. Inherent in the construction of these control charts is the assumption that the sampled process is a normal distribution whose observations are independent and identically distributed (iid). Many processes such as those found in chemical manufacturing, refinery operations, smelting operations, wood product manufacturing, waste-water processing and the operation of nuclear reactors have been shown to have autocorrelated observations. Autocorrelation, which violates the independence assumption of standard control charts, is known to have an adverse effect on the average run length (ARL) performance of control charts. This paper will consider a statistical testing procedure for the change-point problem for monitoring the level parameter of the AR(1) process. This test is shown to result in a CUSUM-based control chart. Two different solutions of the change-point problem are given which result in slightly different control charts. The average run length of each of these CUSUM control charts is found via the Markov chain approach. A methodology for designing the CUSUM-based control chart is presented and the performance of these control charts is compared to other approaches in the literature.

Journal

IISE Transactions – Taylor & Francis

Published: Jun 1, 1998

There are no references for this article.