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Statistical Inference on Availability of Repairable Systems with Standby and Imperfect Coverage
Warm standby component
|引用:||[ 1 ] B.N. Masters, T.O. Lewis, W.J. Kolarik, (1992), A confidence interval for the availability ratio for systems with Weibull operating time and lognormal repair time. Microelectronics and Reliability 32 89-99. [ 2 ] V. Sridharan and P. Mohanavadivu, (1998), Some statistical characteristics of a repairable, standby, humanand machine system, IEEE Transactions on Reliability 47 (4) 431-435. [ 3 ] V.S.S. Yadavalli, M. Botha and A.Bekker, (2002), Asymptotic Confidence Limits for the Steady State Availability of a Two-Unit Parallel System with Preparation Time for the Repair Facility, Asia-Pcific Journal of Operation Research 19 249-256. [ 4 ] P. Chandrasekhar, R. Natarajan, and V.S.S. Yadavalli, (2004), A study on a two unit standby system with Erlangian repair time, Asia-Pacific Journal of Operation Rearch 42 (3) 401-407. [ 5 ] Y.H. Chien, J.C. Ke, and S.L. Lee, (2006), Asymptotic confidence limits for performance measues of repairable system with imperfect service station, Communication in Statistics-Simultion and Computation 35 813-830. [ 6 ] J.C. Ke, S.L. Lee, and Y.L. Hsu, (2007), Bayesian Analysis for a Redundant Repairable System with Imperfect Coverage, Communications in Statistics-Simulation and Computation (in press). [ 7 ] K.H. Wang, L.W. Chiu, (2006), Cost Benefit Analysis of Availability Systems with Warm Standby Units and Imperfect Coverage. Applied Mathematics and Computation 172 (2) 1239-1256. [ 8 ] K.S. Trivedi, (2002), Probability and Statistics with Reliability, Queueing and Computer Science Applications, Second Edition, John Wiley and Sons, Inc. 21 CHAPTER 5. CONCLUSIONS New York. [ 9 ] R.V. Hogg, A.T. Craig, (1995), Introduction to Mathematical Statistics, Prentice-Hall, Inc. [ 10 ] G. Casella, R. L. Berger, (2002), Statistical Inference., 2nd ed., Duxbury Inc. [ 11 ] G.G. Roussas, (1997), A Course in Mathematical Statistics, second ed., Academic Press.|
In this thesis, we study the statistical inference of two availability systems with warm standby components and imperfect coverage. The time-to-failure and time-to-repair of the active and standby components are assumed to be exponential and general distribution, respectively. Assume that the coverage factor is the same for an active-component failure as that for a standby-component failure. Firstly, we propose two consistent and asymptotically normal (CAN) estimators of availability for the two systems, respectively. Based on the CAN estimators of the two availability systems, interval estimation and testing (hypothesis) are performed. To implement the numerical simulation for two availability configurations, we adopt two repair-time distributions, such as lognormal and Weibull distribution. In addition, all simulation results are displayed by appropriate curves for understanding performance of the statistical inference procedures presented in this paper. Finally, numerical comparisons on statistical behaviors for two configurations are drawn.
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