IJSREG Trion Studio
IJSREG

No Publication Cost
Vol 9, No 3:

subscription

Vague Reliability Analysis of Peel Remover Plant by Employing Sugeno’s Fuzzy Failure Rate Technique
Abstract
Generally, classical set theory is used to study the system's reliability. However, classical set theory is not adequate to analyse the genuine situation of the system. One of the excellent theories to capture the information due to subjectivity and vagueness is the fuzzy set theory, as today's modern technique is the result of the consistent development of Science and Engineering Technology. Many mechanical devices in various plants and industries have been advanced through the development of new techniques and sub-systems. The present paper is designed to analyse the vague reliability of mechanical systems, namely the peel remover plant of rice. The peeling plant consists of seven sub-systems. The reliability of the system, measured by using trapezoidal vague numbers (TrapVan) with Sugano’s fuzzy failure rate techniques, is being used to evaluate the reliability of the peel remover plant. A numerical example with a graphical representation is given to present the method.
Full Text
PDF
References
  1. A. Kumar and P. Dhiman; Reliability Estimation of a Network Structure Using Generalized Trapezoidal Fuzzy Numbers. Journal of KONBiN, 51(1), 225-242 (2021).
  2. A. Kumara; S. P. Yadav and S. Kumar; Fuzzy System Reliability Using Different Types of Vague Sets. International Journal of Applied Science and Engineering, 6(1), 71-83 (2008).
  3.  C.H.ChengandD.L.Mon;FuzzySystemReliabilityAnalysisbyIntervalofConfidence.FuzzySetsand Systems, 56, 29-35 (1993).
  4. C.H.ChengandD.L.Mon;FuzzySystemReliabilityAnalysisbyPossibility.MicroelectronicsReliability 33, 587-597 (1993).
  5. C. K. Goel; R. Kishan and D. P. Singh; Reliability Analysis of Gas-Separator System using Boolean Function Technique. Journal of Statistics and Management Systems, 10(1), 55–67 (2007).
  6. D. L. Mon and C. H. Cheng; Fuzzy System Reliability Analysis by Interval of Confidence. Fuzzy Sets System 56, 29-35 (1993).
  7. D. L. Mon and C. H. Cheng; Fuzzy System Reliability Analysis for Components with Different Membership Functions. Fuzzy Sets and System 64, 145-157 (1994).
  8. D. Pandey and M. K. Sharma; Vague Set-Theoretic Approach to Fault Tree Analysis. Journal of International Academy of Physical Sciences, 14(1), 1-14 (2010).
  9. D. Pandey; M. K. Sharma and Rajesh Dangwal; Profust and Posfust Reliability of a Network System. J. Mountain Res., 2, 97-112 (2007).
  10. G. S. Mahapatra and T. K. Roy; Reliability Evaluation using Triangular Intuitionistic Fuzzy Numbers Arithmetic Operations. Proceedings of World Academy of Science, Engineering and Technology, Malaysia, 50, 574-581 (2009).
  11. H. Ying; General Takagi-Sugeno Fuzzy Systems with Simplified Linear Rule Consequent are Universal Controllers, Models, and Filters. Information Sciences, 108, 91–107 (1998).
  12. K. Y. Cai; System Failure, and Fuzzy Methodology: An Introductory Overview. Fuzzy sets and systems, 83, 113-133 (1996).
  13. M. K. Sharma and P. Chaudhary; Reliability Analysis of a System Using Sugeno (TSK) Fuzzy Model. Bulletin of Pure and Applied Sciences. 37E (2) (Math & Stat.), 499-506 (2018).
  14. Mukesh K. Sharma; Vague Reliability of a Network System Using Sugeno’s Fuzzy Failure Rates. IOSR Journal of Engineering, 8(12), 38-48 (2018).
  15. S. Gupta and N. Sharma; Evaluation of Some Reliability Parameters for Solar Panel by Boolean algebra Technique. International Journal of Education and Science Research Review, 1(3), 49-58 (2014).
  16. S. M. Chen; Analyzing Fuzzy System Reliability using Vague Set Theory. Journal of Applied Science and Engineering, 1(1), 82-88 (2003).
  17. S. M. Chen; Fuzzy System Reliability Analysis Based on Vague Set Theory. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, 1650-1655, (1997).
  18. S. M. Chen; Fuzzy System Reliability Analysis using Fuzzy Number Arithmetic Operations. Fuzzy Sets, and Systems, 64, 31-38 (1994).
  19. S. M. Chen; Measures of Similarity between Vague Sets. Fuzzy Sets and Systems, 74, 217-223,(1995).
  20. S. Rajurkar and N. K. Verma; Developing Deep Fuzzy Network with Takagi Sugeno Fuzzy Inference System. IEEE International Conference on Fuzzy Systems, (2017).
  21. W. L. Gau and D. J. Buehrer; Vague sets. IEEE Transactions on Systems, Man, and Cybernetics, 23, 610- 614 (1993).

ISSN(P) 2350-0174

ISSN(O) 2456-2378

Journal Content
Browser