The effect of Phase I sample size on the run length performance of control charts for autocorrelated data

Date

2008-01-01

Author

Köksal, Gülser
Ula, Taylan Ali
Testik, Murat Caner

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

208
views

0
downloads

Traditional control charts assume independence of observations obtained from the monitored process. However, if the observations are autocorrelated, these charts often do not perform as intended by the design requirements. Recently, several control charts have been proposed to deal with autocorrelated observations. The residual chart, modified Shewhart chart, EWMAST chart, and ARMA chart are such charts widely used for monitoring the occurrence of assignable causes in a process when the process exhibits inherent autocorrelation. Besides autocorrelation, one other issue is the unknown values of true process parameters to be used in the control chart design, which are often estimated from a reference sample of in-control observations. Performances of the above-mentioned control charts for autocorrelated processes are significantly affected by the sample size used in a Phase I study to estimate the control chart parameters. In this study, we investigate the effect of Phase I sample size on the run length performance of these four charts for monitoring the changes in the mean of an autocorrelated process, namely an AR(1) process. A discussion of the practical implications of the results and suggestions on the sample size requirements for effective process monitoring are provided.

Subject Keywords

Statistics, Probability and Uncertainty, Statistics and Probability

URI

https://hdl.handle.net/11511/45143

Journal

JOURNAL OF APPLIED STATISTICS

DOI

https://doi.org/10.1080/02664760701683619

Collections

Department of Industrial Engineering, Article

Suggestions

OpenMETU
Core

A marginalized multilevel model for bivariate longitudinal binary data Inan, Gul; İlk Dağ, Özlem (Springer Science and Business Media LLC, 2019-06-01) This study considers analysis of bivariate longitudinal binary data. We propose a model based on marginalized multilevel model framework. The proposed model consists of two levels such that the first level associates the marginal mean of responses with covariates through a logistic regression model and the second level includes subject/time specific random intercepts within a probit regression model. The covariance matrix of multiple correlated time-specific random intercepts for each subject is assumed to ...
Robust estimation and hypothesis testing under short-tailedness and inliers Akkaya, Ayşen (Springer Science and Business Media LLC, 2005-06-01) Estimation and hypothesis testing based on normal samples censored in the middle are developed and shown to be remarkably efficient and robust to symmetric short-tailed distributions and to inliers in a sample. This negates the perception that sample mean and variance are the best robust estimators in such situations (Tiku, 1980; Dunnett, 1982).
Analysis of Covariance with Non-normal Errors ŞENOĞLU, BİRDAL; Avcioglu, Mubeccel Didem (Wiley, 2009-12-01) P>Analysis of covariance techniques have been developed primarily for normally distributed errors. We give solutions when the errors have non-normal distributions. We show that our solutions are efficient and robust. We provide a real-life example.
Models of response error components in supervised interview-reinterview surveys Ayhan, Hüseyin Öztaş (Informa UK Limited, 2003-11-01) The current work deals with modelling of response error components in supervised interview-reinterview surveys. The model considers several stages of an interactive process to obtain and record a response. The response process is evaluated as, controller-interviewer-respondent-interviewer-controller interaction setting under a supervised interviewing process. The allocation of controllers, interviewers and respondents is made by a hierarchical design for the interview-reinterview process. In addition, a cod...
Autoregressive models with short-tailed symmetric distributions Akkaya, Ayşen (Informa UK Limited, 2008-01-01) Symmetric short-tailed distributions do indeed occur in practice but have not received much attention particularly in the context of autoregression. We consider a family of such distributions and derive the modified maximum likelihood estimators of the parameters. We show that the estimators are efficient and robust. We develop hypothesis-testing procedures.

Citation Formats

G. Köksal, T. A. Ula, and M. C. Testik, “The effect of Phase I sample size on the run length performance of control charts for autocorrelated data,” JOURNAL OF APPLIED STATISTICS, pp. 67–87, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/45143.