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Triple Homogeneously Weighted Moving Average Charts for Monitoring Process Dispersion.
- Source :
-
Mathematical Problems in Engineering . 2/3/2023, Vol. 2023, p1-34. 34p. - Publication Year :
- 2023
-
Abstract
- Homogeneously weighted moving average (H W M A) charts have recently achieved popularity for monitoring small changes in process parameters (location and/or dispersion). Furthermore, the D H W M A (double H W M A) and T H W M A (triple H W M A) are the advanced versions of the H W M A charts. The H W M A chart for the process dispersion is designed to detect only the upward (one-sided) shift (i.e., process deterioration). Employing a two-sided chart for concurrently detecting both process improvement and process deterioration is an important aspect of statistical process monitoring. By taking this point as motivation, one and two-sided T H W M A charts (symbolized as the T H W M A V) are proposed for monitoring the process dispersion. The Monte Carlo simulations are performed to investigate the performance behavior of the T H W M A V charts in terms of certain performance indicators, including A R L , S D R L , E Q L , R A R L , and P C I. The comparison among the T H W M A V versus existing charts (D H W M A V , H W M A V , T E W M A V , D E W M A V , and E W M A V) indicates that the T H W M A V charts outperform the existing charts. Finally, a dataset is also analyzed to illustrate the implementation of the T H W M A V charts. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MOVING average process
*MONTE Carlo method
*DISPERSION (Chemistry)
Subjects
Details
- Language :
- English
- ISSN :
- 1024123X
- Volume :
- 2023
- Database :
- Academic Search Index
- Journal :
- Mathematical Problems in Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 161719339
- Full Text :
- https://doi.org/10.1155/2023/6996280