Process Monitoring Using Truncated Gamma Distribution
The time-between-events idea is commonly used for monitoring high-quality processes. This study aims to monitor the increase and/or decrease in the process mean rapidly using a one-sided exponentially weighted moving average (EWMA) chart for the detection of upward or downward mean shifts using a tr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Stats |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-905X/6/4/80 |
| _version_ | 1797379301761351680 |
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| author | Sajid Ali Shayaan Rajput Ismail Shah Hassan Houmani |
| author_facet | Sajid Ali Shayaan Rajput Ismail Shah Hassan Houmani |
| author_sort | Sajid Ali |
| collection | DOAJ |
| description | The time-between-events idea is commonly used for monitoring high-quality processes. This study aims to monitor the increase and/or decrease in the process mean rapidly using a one-sided exponentially weighted moving average (EWMA) chart for the detection of upward or downward mean shifts using a truncated gamma distribution. The use of the truncation method helps to enhance and improve the sensitivity of the proposed chart. The performance of the proposed chart with known and estimated parameters is analyzed by using the run length properties, including the average run length (ARL) and standard deviation run length (SDRL), through extensive Monte Carlo simulation. The numerical results show that the proposed scheme is more sensitive than the existing ones. Finally, the chart is implemented in real-world situations to highlight the significance of the proposed chart. |
| first_indexed | 2024-03-08T20:21:10Z |
| format | Article |
| id | doaj.art-90b1692e0bfe4b85a4706c97dbd0ff60 |
| institution | Directory Open Access Journal |
| issn | 2571-905X |
| language | English |
| last_indexed | 2024-03-08T20:21:10Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Stats |
| spelling | doaj.art-90b1692e0bfe4b85a4706c97dbd0ff602023-12-22T14:43:20ZengMDPI AGStats2571-905X2023-12-01641298132210.3390/stats6040080Process Monitoring Using Truncated Gamma DistributionSajid Ali0Shayaan Rajput1Ismail Shah2Hassan Houmani3Department of Statistics, Quaid-i-Azam University, Islamabad 45320, PakistanDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, PakistanDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, PakistanDepartment of Economics, School of Business, Lebanese International University-LIU, Beirut 146404, LebanonThe time-between-events idea is commonly used for monitoring high-quality processes. This study aims to monitor the increase and/or decrease in the process mean rapidly using a one-sided exponentially weighted moving average (EWMA) chart for the detection of upward or downward mean shifts using a truncated gamma distribution. The use of the truncation method helps to enhance and improve the sensitivity of the proposed chart. The performance of the proposed chart with known and estimated parameters is analyzed by using the run length properties, including the average run length (ARL) and standard deviation run length (SDRL), through extensive Monte Carlo simulation. The numerical results show that the proposed scheme is more sensitive than the existing ones. Finally, the chart is implemented in real-world situations to highlight the significance of the proposed chart.https://www.mdpi.com/2571-905X/6/4/80average run lengthexponentially weighted moving averagestandard deviation of run lengthtime-between-eventstruncated gamma distribution |
| spellingShingle | Sajid Ali Shayaan Rajput Ismail Shah Hassan Houmani Process Monitoring Using Truncated Gamma Distribution Stats average run length exponentially weighted moving average standard deviation of run length time-between-events truncated gamma distribution |
| title | Process Monitoring Using Truncated Gamma Distribution |
| title_full | Process Monitoring Using Truncated Gamma Distribution |
| title_fullStr | Process Monitoring Using Truncated Gamma Distribution |
| title_full_unstemmed | Process Monitoring Using Truncated Gamma Distribution |
| title_short | Process Monitoring Using Truncated Gamma Distribution |
| title_sort | process monitoring using truncated gamma distribution |
| topic | average run length exponentially weighted moving average standard deviation of run length time-between-events truncated gamma distribution |
| url | https://www.mdpi.com/2571-905X/6/4/80 |
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