Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution
Abstract Triple modular redundancy (TMR) is a robust technique utilized in safety-critical applications to enhance fault-tolerance and reliability. This article focuses on estimating the distribution parameters of a TMR system under step-stress partially accelerated life tests, where each component...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-41363-3 |
| _version_ | 1797559929722109952 |
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| author | Laila A. Al-Essa Alaa H. Abdel-Hamid Tmader Alballa Atef F. Hashem |
| author_facet | Laila A. Al-Essa Alaa H. Abdel-Hamid Tmader Alballa Atef F. Hashem |
| author_sort | Laila A. Al-Essa |
| collection | DOAJ |
| description | Abstract Triple modular redundancy (TMR) is a robust technique utilized in safety-critical applications to enhance fault-tolerance and reliability. This article focuses on estimating the distribution parameters of a TMR system under step-stress partially accelerated life tests, where each component included in the system follows a Lomax distribution. The study aims to analyze the system’s reliability and mean residual lifetime based on the estimated parameters. Various estimation techniques, including maximum likelihood, percentile, least squares, and maximum product of spacings, are explored. Additionally, the optimal stress change time is determined using two criteria. An illustrative example supported by two actual data sets is presented to showcase the methodology’s application. By conducting Monte Carlo simulations, the assessment of the estimation methods’ effectiveness reveals that the maximum likelihood method outperforms the other three methods in terms of both accuracy and performance, as indicated by the numerical outcomes. This research contributes to the understanding and practical implementation of TMR systems in safety-critical industries, potentially saving lives and preventing catastrophic events. |
| first_indexed | 2024-03-10T17:52:09Z |
| format | Article |
| id | doaj.art-bec069ac081e442c88165213712b4b74 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T17:52:09Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-bec069ac081e442c88165213712b4b742023-11-20T09:19:15ZengNature PortfolioScientific Reports2045-23222023-09-0113111510.1038/s41598-023-41363-3Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distributionLaila A. Al-Essa0Alaa H. Abdel-Hamid1Tmader Alballa2Atef F. Hashem3Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman UniversityMathematics and Computer Science Department, Faculty of Science, Beni-Suef UniversityDepartment of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman UniversityDepartment of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU)Abstract Triple modular redundancy (TMR) is a robust technique utilized in safety-critical applications to enhance fault-tolerance and reliability. This article focuses on estimating the distribution parameters of a TMR system under step-stress partially accelerated life tests, where each component included in the system follows a Lomax distribution. The study aims to analyze the system’s reliability and mean residual lifetime based on the estimated parameters. Various estimation techniques, including maximum likelihood, percentile, least squares, and maximum product of spacings, are explored. Additionally, the optimal stress change time is determined using two criteria. An illustrative example supported by two actual data sets is presented to showcase the methodology’s application. By conducting Monte Carlo simulations, the assessment of the estimation methods’ effectiveness reveals that the maximum likelihood method outperforms the other three methods in terms of both accuracy and performance, as indicated by the numerical outcomes. This research contributes to the understanding and practical implementation of TMR systems in safety-critical industries, potentially saving lives and preventing catastrophic events.https://doi.org/10.1038/s41598-023-41363-3 |
| spellingShingle | Laila A. Al-Essa Alaa H. Abdel-Hamid Tmader Alballa Atef F. Hashem Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution Scientific Reports |
| title | Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution |
| title_full | Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution |
| title_fullStr | Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution |
| title_full_unstemmed | Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution |
| title_short | Reliability analysis of the triple modular redundancy system under step-partially accelerated life tests using Lomax distribution |
| title_sort | reliability analysis of the triple modular redundancy system under step partially accelerated life tests using lomax distribution |
| url | https://doi.org/10.1038/s41598-023-41363-3 |
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