Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters
In usual quality control methods, the quality of a process or product is evaluated by monitoring one or more quality characteristics using their corresponding distributions. However, when the quality characteristic is defined through the relationship between one or more response and independent vari...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9363123/ |
| _version_ | 1811274324188856320 |
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| author | Ali Yeganeh Ali Reza Shadman Ioannis S. Triantafyllou Sandile Charles Shongwe Saddam Akber Abbasi |
| author_facet | Ali Yeganeh Ali Reza Shadman Ioannis S. Triantafyllou Sandile Charles Shongwe Saddam Akber Abbasi |
| author_sort | Ali Yeganeh |
| collection | DOAJ |
| description | In usual quality control methods, the quality of a process or product is evaluated by monitoring one or more quality characteristics using their corresponding distributions. However, when the quality characteristic is defined through the relationship between one or more response and independent variables, the regime is referred to as profiles monitoring. In this article, we improve the performance of the Exponentially Weighted Moving Average Range (EWMAR) control charts, which are implemented for monitoring linear profiles (i.e., intercept, slope and average residual between sample and reference lines) by integrating them with run rules in order to quickly detect various magnitudes of shifts in profile parameters. The validation of the proposed control chart is accomplished by examining its performance using the average run length (ARL) criteria. The proposed EWMAR chart with run rules exhibits a much better performance in detecting small and decreasing shifts than the other competing charts. Finally, an example from multivariate manufacturing industry is employed to illustrate the superiority of the EWMAR chart with run rules. |
| first_indexed | 2024-04-12T23:16:58Z |
| format | Article |
| id | doaj.art-2a6044de834f46ca94d060d61eccc5cd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T23:16:58Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2a6044de834f46ca94d060d61eccc5cd2022-12-22T03:12:38ZengIEEEIEEE Access2169-35362021-01-019385033852110.1109/ACCESS.2021.30619909363123Run Rules-Based EWMA Charts for Efficient Monitoring of Profile ParametersAli Yeganeh0https://orcid.org/0000-0002-1569-9809Ali Reza Shadman1https://orcid.org/0000-0002-3599-4063Ioannis S. Triantafyllou2https://orcid.org/0000-0002-7512-5217Sandile Charles Shongwe3https://orcid.org/0000-0003-2243-8196Saddam Akber Abbasi4https://orcid.org/0000-0003-1843-8863Department of Industrial Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, IranDepartment of Industrial Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, IranDepartment of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, GreeceDepartment of Statistics, College of Science, Engineering and Technology, University of South Africa, Pretoria, South AfricaDepartment of Mathematics, Statistics and Physics, Qatar University, Doha, QatarIn usual quality control methods, the quality of a process or product is evaluated by monitoring one or more quality characteristics using their corresponding distributions. However, when the quality characteristic is defined through the relationship between one or more response and independent variables, the regime is referred to as profiles monitoring. In this article, we improve the performance of the Exponentially Weighted Moving Average Range (EWMAR) control charts, which are implemented for monitoring linear profiles (i.e., intercept, slope and average residual between sample and reference lines) by integrating them with run rules in order to quickly detect various magnitudes of shifts in profile parameters. The validation of the proposed control chart is accomplished by examining its performance using the average run length (ARL) criteria. The proposed EWMAR chart with run rules exhibits a much better performance in detecting small and decreasing shifts than the other competing charts. Finally, an example from multivariate manufacturing industry is employed to illustrate the superiority of the EWMAR chart with run rules.https://ieeexplore.ieee.org/document/9363123/Control chartlinear profilesphase IIprofile monitoringrun rules scheme |
| spellingShingle | Ali Yeganeh Ali Reza Shadman Ioannis S. Triantafyllou Sandile Charles Shongwe Saddam Akber Abbasi Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters IEEE Access Control chart linear profiles phase II profile monitoring run rules scheme |
| title | Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters |
| title_full | Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters |
| title_fullStr | Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters |
| title_full_unstemmed | Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters |
| title_short | Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters |
| title_sort | run rules based ewma charts for efficient monitoring of profile parameters |
| topic | Control chart linear profiles phase II profile monitoring run rules scheme |
| url | https://ieeexplore.ieee.org/document/9363123/ |
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