Abstract
The moving average (MA), exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are popular control charts to detect small shifts quickly in process parameters. In this study, we evaluate the performance of the EWMA chart for monitoring exponentially distributed quality characteristics based on moving average statistics. The average run length and some other associated characteristics are used as performance measures of the chart. The concept of using the probability of detection for the performance assessment of this chart has been criticized in this study. A real-life application is also provided for practical consideration.
| Original language | English |
|---|---|
| Pages (from-to) | 365-372 |
| Number of pages | 8 |
| Journal | Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an |
| Volume | 43 |
| Issue number | 4 |
| DOIs | |
| State | Published - 18 May 2020 |
Bibliographical note
Publisher Copyright:© 2020, © 2020 The Chinese Institute of Engineers.
Keywords
- EWMA chart
- Monte Carlo simulation
- exponential distribution
- moving average
- probability of detection
- run length
ASJC Scopus subject areas
- General Engineering
Fingerprint
Dive into the research topics of 'Performance evaluation of moving average-based EWMA chart for exponentially distributed process'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver