Performance Analysis of Multi-State k-out-of-n System using Sumudu Transform with Fermatean Fuzzy Sets.

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Title: Performance Analysis of Multi-State k-out-of-n System using Sumudu Transform with Fermatean Fuzzy Sets.
Authors: G., Hemalatha1, G., Vijayalakshmi1 vijayalg@srmist.edu.in
Source: International Journal of Performability Engineering. Dec2025, Vol. 21 Issue 12, p714-724. 11p.
Subjects: Reliability in engineering, Systems availability, Fault-tolerant control systems, Stochastic systems, Stochastic processes, Operations research, Fuzzy sets, Integral transforms
Abstract: This research investigates the reliability and availability of a multi-state k-out-of-n system composed of three interconnected subsystems: main power supply units, backup generators, and uninterruptible power supply units. Each subsystem operates under specific failure and repair protocols, including warm and cold standby arrangements. State transitions are modeled using stochastic processes, and the Sumudu transform technique is employed to solve the complex differential equations governing the system's behavior. Fermatean fuzzy sets are incorporated to effectively manage uncertainty. Numerical illustrations evaluate availability and reliability under various scenarios, demonstrating the influence of failure rates, maintenance delays, and repair personnel availability on system performance. The fuzzy approach provides a broader range of reliability and availability estimates compared to traditional Markov methods. The integration of advanced mathematical tools and Fermatean fuzzy logic enhances decision-making, maintenance planning, and cost optimization, enabling the design of robust, efficient, and cost-effective systems in complex engineering environments with prevalent uncertainties. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Performability Engineering is the property of Totem Publisher, Inc. 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.)
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  Data: <searchLink fieldCode="DE" term="%22Reliability+in+engineering%22">Reliability in engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+availability%22">Systems availability</searchLink><br /><searchLink fieldCode="DE" term="%22Fault-tolerant+control+systems%22">Fault-tolerant control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Stochastic+systems%22">Stochastic systems</searchLink><br /><searchLink fieldCode="DE" term="%22Stochastic+processes%22">Stochastic processes</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+research%22">Operations research</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+sets%22">Fuzzy sets</searchLink><br /><searchLink fieldCode="DE" term="%22Integral+transforms%22">Integral transforms</searchLink>
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  Data: This research investigates the reliability and availability of a multi-state k-out-of-n system composed of three interconnected subsystems: main power supply units, backup generators, and uninterruptible power supply units. Each subsystem operates under specific failure and repair protocols, including warm and cold standby arrangements. State transitions are modeled using stochastic processes, and the Sumudu transform technique is employed to solve the complex differential equations governing the system's behavior. Fermatean fuzzy sets are incorporated to effectively manage uncertainty. Numerical illustrations evaluate availability and reliability under various scenarios, demonstrating the influence of failure rates, maintenance delays, and repair personnel availability on system performance. The fuzzy approach provides a broader range of reliability and availability estimates compared to traditional Markov methods. The integration of advanced mathematical tools and Fermatean fuzzy logic enhances decision-making, maintenance planning, and cost optimization, enabling the design of robust, efficient, and cost-effective systems in complex engineering environments with prevalent uncertainties. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Performability Engineering is the property of Totem Publisher, Inc. 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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      – Type: doi
        Value: 10.23940/ijpe.25.12.p5.714724
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 714
    Subjects:
      – SubjectFull: Reliability in engineering
        Type: general
      – SubjectFull: Systems availability
        Type: general
      – SubjectFull: Fault-tolerant control systems
        Type: general
      – SubjectFull: Stochastic systems
        Type: general
      – SubjectFull: Stochastic processes
        Type: general
      – SubjectFull: Operations research
        Type: general
      – SubjectFull: Fuzzy sets
        Type: general
      – SubjectFull: Integral transforms
        Type: general
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      – TitleFull: Performance Analysis of Multi-State k-out-of-n System using Sumudu Transform with Fermatean Fuzzy Sets.
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            NameFull: G., Hemalatha
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            NameFull: G., Vijayalakshmi
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            – D: 01
              M: 12
              Text: Dec2025
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              Y: 2025
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            – TitleFull: International Journal of Performability Engineering
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