Improving, calculating and projecting the reliability of products is a fundamental task nowadays in the industry. The most common stochastic process models in the literature and applications are the Gamma and Wiener processes. However, both models are insufficient to adjust all degradation data. There are applications where they do not fit at all and can lead to erroneous conclusions. In this manner, the Gaussian inverse process is a very attractive option for degradation data. In order to compare the Wiener, gamma and Gaussian inverse processes, we searched for written literature (books and articles) and online data-bases (virtual libraries, Academic Google and different data bases) for which some applications were obtained in different areas of study and the tendency of the use of the different processes through the last years. In addition, to identify characteristics and differences between each of the stochastic processes.

Keywords: Reliability, Degradation model, Stochastic process degradation, Gamma processes degradation, Inverse Gaussian Process degradation, Wiener Process degradation