{"title":"Reliability Analysis of k-out-of-n : G System Using Triangular Intuitionistic Fuzzy Numbers","authors":"Tanuj Kumar, Rakesh Kumar Bajaj","volume":86,"journal":"International Journal of Mathematical and Computational Sciences","pagesStart":373,"pagesEnd":380,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/9997595","abstract":"<p>In the present paper, we analyze the vague reliability of k-out-of-n : G system (particularly, series and parallel system) with independent and non-identically distributed components, where the reliability of the components are unknown. The reliability of each component has been estimated using statistical confidence interval approach. Then we converted these statistical confidence interval into triangular intuitionistic fuzzy numbers. Based on these triangular intuitionistic fuzzy numbers, the reliability of the k-out-of-n : G system has been calculated. Further, in order to implement the proposed methodology and to analyze the results of k-out-of-n : G system, a numerical example has been provided.<\/p>\r\n","references":"[1] K. Atanassov, \"lntuitionistic fuzzy sets,\u201d VII ITKR\u2019s Session, Deposed in Central Sci.- Techn. Library of Bulg. Acd. of Sci. Sofia, pp. 1677\u201384, 1983.\r\n[2] K. Atanassov, \"Intuitionistic fuzzy sets,\u201d Fuzzy Sets and Systems, vol. 20(1), pp.87-96, 1986.\r\n[3] K. Atanassov and G. Gargov, \"Interval-valued intuitionistic fuzzy sets,\u201d Fuzzy Sets and Systems, vol. 31(3), 343-349, 1989.\r\n[4] RE Barlow and KD. Heidtmann, \"Computing k-out-of-n system reliability,\u201d IEEE Trans. on Reliability, vol. R-33, pp. 322-323, 1984.\r\n[5] P. Burillo, H. Bustince, and V. Mohedano, \"Some Definition of Intuitionistic Fuzzy Number First Properties,\u201d Proc. of the First Workshop on Fuzzy based expert systems, pp. 53\u201355, Sofia, Bulgaria, September 1994.\r\n[6] H. Bustince and P. 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