Author(s): K. Uma Maheswari, K. Subrahmanyam, A. Mallikarjuna Reddy

Email(s): subrahmanyamkothagundu@gmail.com , arekantiraju@gmail.com , arekantiraju@gmail.com

DOI: 10.52711/2321-5828.2021.00024   

Address: Dr. K. Uma Maheswari1, K. Subrahmanyam2, Dr. A. Mallikarjuna Reddy3
1Associate Professor, Dept of Humanities and Sciences, Srinivasa Ramanujan Institute of Technology, Anantapur, Andhra Pradesh India.
2Dept of Mechanical Engineering, JNTUA College of Engineering, Anantapur, Andhra Pradesh India.
3Professor, Dept of Mathematics, Sri Krishnadevaraya University, Anantapur, Andhra Pradesh India.
*Corresponding Author

Published In:   Volume - 12,      Issue - 3,     Year - 2021


ABSTRACT:
Large amounts of money are lost each year in the real-estate industry because of poor schedule and cost control, In Industry the investigated failure and repair pattern, reliabilities of generators, compressors, turbines, using simple statistical tools and simulation techniques. The repair duration is divided into the 1) Major repair 2) Minor repair, In major repair having (repair hour greater than a threshold valve) and Minor repair having (repair hour less than (or)equal to threshold valve). This approach is mainly for Weibull distribution method. In Weibull analysis is a common method for failure analysis and reliability engineering used in a wide range of applications. In this paper, the applicability of Weibull analysis for evaluating and comparing the reliability of the schedule performance of multiple projects is presented, while the successive performance of multiple projects is presented, while the successive repair times are increasing and are exposing to Weibull distribution, under these assumptions, an optimal replacement policy ‘T’ in which we replace the system, when the repair time reaches T. It can be determined that an optimal repair replacement policy T* such that long run average cost and the corresponding optimal replacement policy T* can be determined analytically.


Cite this article:
K. Uma Maheswari, K. Subrahmanyam, A. Mallikarjuna Reddy. Cataloging of Unit Replacement Based on Long Run Repair Average Cost Rate (ACR) Based on Weibull Distribution Model. Research Journal of Humanities and Social Sciences. 2021; 12(3):149-2. doi: 10.52711/2321-5828.2021.00024

Cite(Electronic):
K. Uma Maheswari, K. Subrahmanyam, A. Mallikarjuna Reddy. Cataloging of Unit Replacement Based on Long Run Repair Average Cost Rate (ACR) Based on Weibull Distribution Model. Research Journal of Humanities and Social Sciences. 2021; 12(3):149-2. doi: 10.52711/2321-5828.2021.00024   Available on: https://rjhssonline.com/AbstractView.aspx?PID=2021-12-3-4


REFERENCES:
1.    Reddy, A. M., and Joshna, N. (2017). Identification of Unit Replacement Based on Long-Run Repair Average Cost Rate (Acr) Based on Truncated Exponential Failure Model. Bulletin of Pure and Applied Sciences- Mathematics and Statistics, 36e(1), 37.
2.    Barlow,R.E,’Operation Research, vol.08, pp.90-100, 1959
3.    Barlow, R.E,’Mathematical Theory of Reability’,1965
4.    Devasena, G. S. (2017). key words: Alpha series Dr. B. Venkata Ramudu, (5), 6–8. Retrieved
5.    www.semanticscholar.org. (n.d.). Retrieved from
6.    Bal Guruswamy, Reliability Engineering, Tata Mc Graw Hill, New delhi,1984.
7.    Dhillon B.S Reliability Engineering applications areas beta publishers Gloucester 1992.
8.    Srinath L.S Reliability Engineering East West Press New Delhi 2013.
9.    Reni Sargunaraj M Marline Anita A Chandrababu. A Shanmugam Priya’s
10.    wai-ki-ching Michael k.Ng Markov Chains Models Algorithms and Applications, Springer international New Delhi 2008.

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