Academic Journal
Analysis of failure data for estimating availability and reliability indicators using statistical and stochastic methods.
| Title: | Analysis of failure data for estimating availability and reliability indicators using statistical and stochastic methods. |
|---|---|
| Authors: | KONWERSKI, Jakub, ZIÓŁKOWSKI, Jarosław, OSZCZYPAŁA, Mateusz, MAŁACHOWSKI, Jerzy, LĘGAS, Aleksandra |
| Source: | Maintenance & Reliability / Eksploatacja i Niezawodność; 2026, Vol. 28 Issue 2, p1-22, 22p |
| Subject Terms: | Markov processes, Stochastic analysis, Engineering systems, Maintainability (Engineering), Failure analysis, Mathematical statistics, Reliability in engineering |
| Abstract: | This paper presents a novel implementation of statistical and stochastic methods for estimating and evaluating reliability and availability indicators in technical systems. Using empirical failure data from a realworld military transport system, we introduce an innovative 7-state model that provides a detailed representation of operational phase of the systems. The research integrates Markov and semi-Markov processes to accurately model state transitions, particularly addressing scenarios where traditional Markov models are insufficient due to non-exponential state distributions. Our findings demonstrate that both statistical and stochastic methods yield closely aligned reliability and availability indicators, validating the robustness of the proposed methodologies. This research not only advances the accuracy of reliability assessments but also identifies actionable improvements to enhance operational readiness. They provide a comprehensive framework for analyzing and improving the operational efficiency of technical systems, with broader applications across various engineering fields. [ABSTRACT FROM AUTHOR] |
| Copyright of Maintenance & Reliability / Eksploatacja i Niezawodność is the property of Polish Scientific & Technical Society Consumables, Polish Maintenance Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
| FullText | Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 192185233 RelevancyScore: 1061 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1060.75964355469 |
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| Items | – Name: Title Label: Title Group: Ti Data: Analysis of failure data for estimating availability and reliability indicators using statistical and stochastic methods. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22KONWERSKI%2C+Jakub%22">KONWERSKI, Jakub</searchLink><br /><searchLink fieldCode="AR" term="%22ZIÓŁKOWSKI%2C+Jarosław%22">ZIÓŁKOWSKI, Jarosław</searchLink><br /><searchLink fieldCode="AR" term="%22OSZCZYPAŁA%2C+Mateusz%22">OSZCZYPAŁA, Mateusz</searchLink><br /><searchLink fieldCode="AR" term="%22MAŁACHOWSKI%2C+Jerzy%22">MAŁACHOWSKI, Jerzy</searchLink><br /><searchLink fieldCode="AR" term="%22LĘGAS%2C+Aleksandra%22">LĘGAS, Aleksandra</searchLink> – Name: TitleSource Label: Source Group: Src Data: Maintenance & Reliability / Eksploatacja i Niezawodność; 2026, Vol. 28 Issue 2, p1-22, 22p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink><br /><searchLink fieldCode="DE" term="%22Stochastic+analysis%22">Stochastic analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+systems%22">Engineering systems</searchLink><br /><searchLink fieldCode="DE" term="%22Maintainability+%28Engineering%29%22">Maintainability (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Failure+analysis%22">Failure analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+statistics%22">Mathematical statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Reliability+in+engineering%22">Reliability in engineering</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper presents a novel implementation of statistical and stochastic methods for estimating and evaluating reliability and availability indicators in technical systems. Using empirical failure data from a realworld military transport system, we introduce an innovative 7-state model that provides a detailed representation of operational phase of the systems. The research integrates Markov and semi-Markov processes to accurately model state transitions, particularly addressing scenarios where traditional Markov models are insufficient due to non-exponential state distributions. Our findings demonstrate that both statistical and stochastic methods yield closely aligned reliability and availability indicators, validating the robustness of the proposed methodologies. This research not only advances the accuracy of reliability assessments but also identifies actionable improvements to enhance operational readiness. They provide a comprehensive framework for analyzing and improving the operational efficiency of technical systems, with broader applications across various engineering fields. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Maintenance & Reliability / Eksploatacja i Niezawodność is the property of Polish Scientific & Technical Society Consumables, Polish Maintenance Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.17531/ein/211577 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 1 Subjects: – SubjectFull: Markov processes Type: general – SubjectFull: Stochastic analysis Type: general – SubjectFull: Engineering systems Type: general – SubjectFull: Maintainability (Engineering) Type: general – SubjectFull: Failure analysis Type: general – SubjectFull: Mathematical statistics Type: general – SubjectFull: Reliability in engineering Type: general Titles: – TitleFull: Analysis of failure data for estimating availability and reliability indicators using statistical and stochastic methods. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: KONWERSKI, Jakub – PersonEntity: Name: NameFull: ZIÓŁKOWSKI, Jarosław – PersonEntity: Name: NameFull: OSZCZYPAŁA, Mateusz – PersonEntity: Name: NameFull: MAŁACHOWSKI, Jerzy – PersonEntity: Name: NameFull: LĘGAS, Aleksandra IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 15072711 Numbering: – Type: volume Value: 28 – Type: issue Value: 2 Titles: – TitleFull: Maintenance & Reliability / Eksploatacja i Niezawodność Type: main |
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