Reliability estimation in multicomponent stress-strength based on Erlang-truncated exponential distribution
International Journal of Quality & Reliability Management
ISSN: 0265-671X
Article publication date: 6 March 2017
Abstract
Purpose
The purpose of this paper is to consider the estimation of multicomponent stress-strength reliability. The system is regarded as alive only if at least s out of k (s<k) strengths exceed the stress. The reliability of such a system is obtained when strength, stress variates are from Erlang-truncated exponential (ETE) distribution with different shape parameters. The reliability is estimated using the maximum likelihood (ML) method of estimation when samples are drawn from strength and stress distributions. The reliability estimators are compared asymptotically. The small sample comparison of the reliability estimates is made through Monte Carlo simulation. Using real data sets the authors illustrate the procedure.
Design/methodology/approach
The authors have developed multicomponent stress-strength reliability based on ETE distribution. To estimate reliability, the parameters are estimated by using ML method.
Findings
The simulation results indicate that the average bias and average mean square error decreases as sample size increases for both methods of estimation in reliability. The length of the confidence interval also decreases as the sample size increases and simulated actual coverage probability is close to the nominal value in all sets of parameters considered here. Using real data, the authors illustrate the estimation process.
Originality/value
This research work has conducted independently and the results of the author’s research work are very useful for fresh researchers.
Keywords
Citation
Gadde, S.R. (2017), "Reliability estimation in multicomponent stress-strength based on Erlang-truncated exponential distribution", International Journal of Quality & Reliability Management, Vol. 34 No. 3, pp. 438-445. https://doi.org/10.1108/IJQRM-11-2012-0147
Publisher
:Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited