System Reliability Estimation with Two Types of Common Cause Shock Failures
Main Article Content
Abstract
This paper discusses the reliability analysis of a three component identical system. The system may affects by two types of failures viz., Lethal Common Cause Shock (LCCS) and Non-Lethal Common Cause Shock (NCCS) failures. By using stochastic process, the set of differential equations of the existing model are derived to attain reliability measures such as system reliability and Mean Time to Failure (MTTF) in both series and parallel cases. In addition, the Maximum Likelihood Estimates (MLE) of the above said measures are derived and shown in numerical illustration by using simulation process. The numerical tables shows the outcomes and recommend that LCCS and NCCS are the most leading causes of failures while studying the performance of the systems in reliability theory.
Downloads
Metrics
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
References
R. Billinton and R. N. Allan, Reliability evaluation of engineering systems: concepts and techniques, Plenum Press, New York, 1983.
A. A. Chari, M. P. Sastry, and S. Madhusudhana Verma, “Reliability analysis in the presence of common cause shock failures,” Micro-Electronics and
reliability, vol. 31, pp. 15-19, 1991
B. S. Dhillon, “On common cause failures-bibliography,” Micro Electronics and Reliability, vol. 18, pp. 533-534, 1978.
B. S. Dhillon, “Modeling human errors in repairable systems,” in Proc. Annual Reliability and Maintainability Symposium, 1989, pp. 418-424.
Y. R. Reddy, “Reliability analysis for two unit non-identical system with CCS failures,” Ph. D thesis, S. K. University, Anantapur, India,
S. M. Verma and A. A. Chari, Availability and frequency of failures of a system in the presence of chance common cause shock failures, MicroElectronics and reliability, vol. 31, pp. 265 – 269, 1991.
G. Y. Sagar, K. Awgichew, M. F. Melkamu and S. M. Abdulfeta, “Simulation Study on Reliability Estimates of a Repairable System with Lethal and
Non-Lethal Common Cause Shock Failures,” Elixir Statistics, vol.126, pp. 52481-52484, 2019.
K. Awgichew and G. Y. Sagar, “Estimation of Availability Measures and Confidence Interval for two unit system with Common Cause Shock failures
and Human Errors,” IOSR Journal of Mathematics (IOSR-JM), Vol. 14(3), pp. 52-59, 2018.
G. Y. Sagar, “Frequency of Failures of a System and Confidence-interval,” Elixir Statistics, vol. 70, pp. 23818-23821, 2014.
B. R. Sreedhar, G. Y. Sagar, K. Pushpanjali, and Y. R. Reddy, “M L Estimation of the reliability measures of a two unit system in the presence of two
kinds of CCS failures,” ARPN Journal of Engineering and Applied Sciences, vol. 7(8), pp. 980 – 986, 2012.
B. R. Sreedhar, K. Pushpanjali, G. Y. Sagar, and Y. R. Reddy, “Evaluation of System Availability and Frequency of Failures with Lethal and NonLethal
CCS Failures By Maximum Likelihood Estimation,” International Journal of Engineering Science and Technology (IJEST), vol. 4(6), pp. 2677-2691,
June 2012.