Author(s):
1. Ayesha Talib:
Quaid-i-Azam University,Islamabad, Pakistan.
2. Sajid Ali:
Quaid-i-Azam University,Islamabad, Pakistan.
3. Ismail Shah:
University of Padua,Padova,Italy
Abstract:
Control charts are sophisticated graphical tools used to detect and control aberrant variations. Different control schemes are designed to continuously monitor and improve the process stability and performance. This study proposes a bivariate exponentially weighted moving average chart for joint monitoring of the mean vector of Gumbel’s bivariate geometric (GBG) data. The performance of the proposed chart is compared with the Hotelling’s T2 chart. The results of the study indicated that the proposed control chart performs uniformly and substantially better than the Hotelling’s T2 chart. In addition to two real-life examples, an example based on simulated data is also considered and compared to existing charts to verify the superiority of the proposed chart. Based on the comparisons, it turns out that the MEWMA (GBG) chart outperforms the Hotelling’s T2 chart and paired individual EWMA control chart.
Page(s):
193-193
DOI:
DOI not available
Published:
Journal: 4th International Conference of Sciences “Revamped Scientific Outlook of 21st Century, 2025” , November 12,2025, Volume: 1, Issue: 1, Year: 2025
Keywords:
Average Run Length
,
control chart
,
exponentially weighted moving average
,
bivariate Gumbel distribution
,
Basu Dhar distribution
References:
References are not available for this document.
Citations
Citations are not available for this document.