Modeling Reliability
Reliability Estimation for the Exponential Distribution using Maximum likelihood and Bayes Method
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The aim of this study is to apply lifetime models on the failure time of automatic teller machines (ATM) in Sudan and to estimate the reliability of machines, in order to compare between machines and methods of estimation, through use the failure models and the suitable statistical methods for failure data analysis. The comparison between methods of estimation has executed through mean square error values (MSE).And the most important results found out by researcher are: The mean square error values (MSE) of exponential parameter which is estimated by Maximum likelihood method is less than MSE ...
The aim of this study is to apply lifetime models on the failure time of automatic teller machines (ATM) in Sudan and to estimate the reliability of machines, in order to compare between machines and methods of estimation, through use the failure models and the suitable statistical methods for failure data analysis. The comparison between methods of estimation has executed through mean square error values (MSE).And the most important results found out by researcher are: The mean square error values (MSE) of exponential parameter which is estimated by Maximum likelihood method is less than MSE of Bayes' estimator or the Maximum likelihood method is better than Bayes method in estimate the parameter and the reliability function for exponential distribution of automatic teller machines (ATM) in Sudan, The machines with high reliability have a low faults probability and hazard rate, while the machines with low reliability have a high fault probability and hazard rate, Whenever the mean time to failure for machine increases it indicates that the machine has high reliability and the reliability of the machines decreases when the working time of machines increases.
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