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

Author

Listed:
  • S Golui
  • BS Mahapatra
  • GS Mahapatra

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 ( α , β ) − cuts of TPFN and TrPFN.

Suggested Citation

  • S Golui & BS Mahapatra & GS Mahapatra, 2025. "System reliability analysis of thermal power plant using novel approach to pythagorean fuzzy numbers operations," Journal of Risk and Reliability, , vol. 239(6), pages 1346-1363, December.
    • Handle: RePEc:sae:risrel:v:239:y:2025:i:6:p:1346-1363
    DOI: 10.1177/1748006X251329424
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    References listed on IDEAS

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    1. Postnikov, Ivan, 2022. "A reliability assessment of the heating from a hybrid energy source based on combined heat and power and wind power plants," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    2. Mohammad Nadjafi & Mohammad Ali Farsi, 2021. "Reliability analysis of system with timing functional dependency using fuzzy-bathtub failure rates," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(5), pages 919-930, October.
    3. Haipeng Wang & Fuhai Duan, 2019. "Reliability analysis method of the uncertain system based on fuzzy GO methodology and its application in electro-hydrostatic actuator," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 1265-1275, October.
    4. Garmabaki, A.H.S. & Ahmadi, Alireza & Block, Jan & Pham, Hoang & Kumar, Uday, 2016. "A reliability decision framework for multiple repairable units," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 78-88.
    5. Chaube, Shshank & Joshi, Dheeraj Kumar & Ujarari, Chandan Singh, 2023. "Hesitant Bifuzzy Set (an introduction): A new approach to assess the reliability of the systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 98-107.
    6. Daniel O. Aikhuele & Grace Ijele-Aikhuele, 2022. "Development of a hybrid reliability-centered model for escalator systems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 761-771, April.
    7. Maneckshaw, B. & Mahapatra, G.S., 2024. "Crossover point analysis with Jensen-Shannon divergence lower bound for bi-objective reliability optimization of k-out-of-n system," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    8. Qin He & Ruijun Zhang & Tianyu Liu & Yabing Zha & Jie Liu, 2019. "Multi-state system reliability analysis methods based on Bayesian networks merging dynamic and fuzzy fault information," International Journal of Reliability and Safety, Inderscience Enterprises Ltd, vol. 13(1/2), pages 44-60.
    9. E. El-Ghamry & M. El-Damsece & M. Shokry, 2020. "Reliability analysis of different systems using triangular multi-fuzzy sets estimated by statistical data," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 16(4), pages 499-514.
    10. Mintu Kumar & S. B. Singh, 2024. "Analysis of system reliability based on weakest t-norm arithmetic operations using Pythagorean fuzzy numbers," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(4), pages 1467-1482, April.
    11. Subhashis Chatterjee & Jeetendra B. Singh & Arunava Roy, 2015. "A structure-based software reliability allocation using fuzzy analytic hierarchy process," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(3), pages 513-525, February.
    12. Chen, Zhiwei & Zhang, Hao & Wang, Xinyue & Yang, Jinling & Dui, Hongyan, 2024. "Reliability analysis and redundancy design of satellite communication system based on a novel Bayesian environmental importance," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    13. Neha & Vibha Verma & Abhishek Tandon & Anu G. Aggarwal, 2021. "Software reliability allocation incorporating Pythagorean fuzzy theory and AHP," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 38(1), pages 19-34.
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