System reliability analysis of thermal power plant using novel approach to pythagorean fuzzy numbers operations

The global community thoroughly evaluates several renewable energy sources but has yet to completely replace conventional energy sources. Thermal power plants (TPPs) are the predominant electrical energy generators among the primary energy sources. Consequently, the researcher had the critical task of conducting a reliability study of TPPs throughout the design and production phase. The evaluation of the TPPs’ system reliability becomes a complex and uncertain challenge owing to the uncertainty associated with the reliability of the TPPs’ components. The assessment of component reliability in a complex system relies on recorded data, which compels technologists to scrutinize the idea of imprecise reliability analysis. This article presents a novel approach to assessing the system’s reliability under uncertain settings. It focuses on performing arithmetic operations on triangular Pythagorean fuzzy numbers (TPFNs) and trapezoidal Pythagorean fuzzy numbers (TrPFNs). TPFNs and TrPFNs are extensions of Pythagorean fuzzy numbers that provide a more precise depiction of uncertainty than standard fuzzy sets. The proposed arithmetic operations evaluate the reliability of different system topologies, including series, parallel, and complex systems. The numerical demonstration is shown by using the suggested processes to assess the reliability of a TPP. The effectiveness of the suggested arithmetic operations on TPFNs and TrPFNs is shown by their ability to decrease uncertainty compared to the conventional approach of using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>α</mml:mi> <mml:mo>,</mml:mo> <mml:mspace width="0.25em"/> <mml:mi>β</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>−</mml:mo> </mml:mrow> </mml:math> cuts of TPFN and TrPFN.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
Published
2025-04-29
DOI
https://doi.org/10.1177/1748006x251329424
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

System reliability analysis of thermal power plant using novel approach to pythagorean fuzzy numbers operations

G. S. Mahapatra, B. S. Mahapatra, S. Golui
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
Multi-Criteria Decision Making
article

System reliability analysis of thermal power plant using novel approach to pythagorean fuzzy numbers operations

G. S. Mahapatra, B. S. Mahapatra, S. Golui
article en

Abstract

The global community thoroughly evaluates several renewable energy sources but has yet to completely replace conventional energy sources. Thermal power plants (TPPs) are the predominant electrical energy generators among the primary energy sources. Consequently, the researcher had the critical task of conducting a reliability study of TPPs throughout the design and production phase. The evaluation of the TPPs’ system reliability becomes a complex and uncertain challenge owing to the uncertainty associated with the reliability of the TPPs’ components. The assessment of component reliability in a complex system relies on recorded data, which compels technologists to scrutinize the idea of imprecise reliability analysis. This article presents a novel approach to assessing the system’s reliability under uncertain settings. It focuses on performing arithmetic operations on triangular Pythagorean fuzzy numbers (TPFNs) and trapezoidal Pythagorean fuzzy numbers (TrPFNs). TPFNs and TrPFNs are extensions of Pythagorean fuzzy numbers that provide a more precise depiction of uncertainty than standard fuzzy sets. The proposed arithmetic operations evaluate the reliability of different system topologies, including series, parallel, and complex systems. The numerical demonstration is shown by using the suggested processes to assess the reliability of a TPP. The effectiveness of the suggested arithmetic operations on TPFNs and TrPFNs is shown by their ability to decrease uncertainty compared to the conventional approach of using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>α</mml:mi> <mml:mo>,</mml:mo> <mml:mspace width="0.25em"/> <mml:mi>β</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>−</mml:mo> </mml:mrow> </mml:math> cuts of TPFN and TrPFN.

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and ReliabilityVol. 239(6)
Haldia Institute of Technology (IN), Maulana Abul Kalam Azad University of Technology, West Bengal (IN)
Openalex Percentile: Top 90%
Multi-Criteria Decision Making
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