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http://dx.doi.org/10.5139/JKSAS.2019.47.10.747

Parameter Estimation of Reliability Growth Model with Incomplete Data Using Bayesian Method  

Park, Cheongeon (School of Aerospace and Mechanical Engineering, Korea Aerospace University)
Lim, Jisung (School of Aerospace and Mechanical Engineering, Korea Aerospace University)
Lee, Sangchul (School of Aerospace and Mechanical Engineering, Korea Aerospace University)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.47, no.10, 2019 , pp. 747-752 More about this Journal
Abstract
By using the failure information and the cumulative test execution time obtained by performing the reliability growth test, it is possible to estimate the parameter of the reliability growth model, and the Mean Time Between Failure (MTBF) of the product can be predicted through the parameter estimation. However the failure information could be acquired periodically or the number of sample data of the obtained failure information could be small. Because there are various constraints such as the cost and time of test or the characteristics of the product. This may cause the error of the parameter estimation of the reliability growth model to increase. In this study, the Bayesian method is applied to estimating the parameters of the reliability growth model when the number of sample data for the fault information is small. Simulation results show that the estimation accuracy of Bayesian method is more accurate than that of Maximum Likelihood Estimation (MLE) respectively in estimation the parameters of the reliability growth model.
Keywords
Reliability Growth Model; AMSAA Model; Bayesian Method; Maximum Likelihood Estimation; Markov Chain Monte Carlo; Mean Squared Error;
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