@article { author = {Givehchi, Saeed and Heidari, Alireza}, title = {Bayes Networks and Fault Tree Analysis Application in Reliability Estimation (Case Study: Automatic Water Sprinkler System)}, journal = {Environmental Energy and Economic Research}, volume = {2}, number = {4}, pages = {325-341}, year = {2018}, publisher = {Environmental Energy and Economic Research}, issn = {2538-4988}, eissn = {2676-4997}, doi = {10.22097/eeer.2019.160566.1057}, abstract = {In this study, the application of Bayes networks and fault tree analysis in reliability estimation have been investigated. Fault tree analysis is one of the most widely used methods for estimating reliability. In recent years, a method called "Bayes Network" has been used, which is a dynamic method, and information about the probable failure of the system components will be updated according to the components data. In other words, the Bayes network is generally distributed with primary values and relations between variables. In this research, the reliability of the automatic Environmental detection and fire extinguisher system by water sprinkler system has been estimated by FTA and BAYES NETWORKS, also their comparison has been investigated. The probabilistic calculation and the graphical drawing required for this research has been completed by MATLAB and MICROSOFT BAYES NETWORK software. Finally, the reliability of an automatic water sprinkler system was calculated 0.93 by FTA. By updating the probability of failure and success, this value was changed to 0.89. The reason for the difference can be interpreted by taking into account the third state of the system, i.e., functioning with lower efficiency. The lowest level of reliability relates to a diesel generator that acts as a standby member in the event of a power failure. At the end, suggestions for improving the reliability of the automatic fire sprinkler system provided.}, keywords = {Bayes networks,Fault Tree Analysis,Reliability,Automatic systems,Fire extinguishing system}, url = {https://www.eeer.ir/article_82625.html}, eprint = {https://www.eeer.ir/article_82625_3c636420559f1a50de68a6ffb3f7908e.pdf} }