<![CDATA[When a reliability function is found for a particular model, attention should be paid to the factors affecting this model, which often divide these factors into the durability factors possessed by the components of the model and the stress factors to which the components of the model are exposed. In this paper, a reliability function was found for one of the stress-robustness models where the model consists of one component that has robustness expressed by the random variable X and is subjected to four stresses expressed by random variables (Y1, Y2, Y3, Y4) assume that the random variables follow the Rayleigh distribution. The distribution parameters were estimated by three methods of estimation (maximum likelihood method, least squares method and weighted least squares method), after which the reliability function of the model was estimated. A Monte Carlo simulation was also performed to compare the results obtained from the estimate using the mean squared error criterion. The comparison showed that ML is the best estimator of the reliability function.]]>
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