Max-Chart for Autocorrelated Processes

Keoagile Thaga, P. M. Kgosi, Lesego Gabaitiri

Research output: Contribution to journalArticlepeer-review

Abstract

Statistical process control procedures are usually implemented under the assumption that the observations from a process are independent over time. However, this assumption is often violated. Therefore, we propose a single Shewhart-type control chart for autocorrelated process by fitting a time series model into the process and monitoring the residuals from the forecast values of a fitted time series model. Numerical results illustrate the ARL of the AR(1) plus random error model, for the cases of step changes in the mean and/or standard deviation. Compared to other charts that monitor autocorrelated processes, this chart quickly detects shifts in the process location and spread particularly for large shifts.
Original languageEnglish
Pages (from-to)87-105
Number of pages19
JournalStochastics and Quality Control
Volume22
Issue number1
Publication statusPublished - 2007

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