Reliability and Maintenance Cost Forecasting for Systems with Multistate Components Using Artificial Neural Networks

In this paper, a study on the use of artificial neural networks for predicting the system reliability and maintenance cost of a system with multistate components is presented. TensorFlow and Keras APIs are used to build and train deep learning models under Python environment. Different numerical experimentations are carried out to illustrate the use of the robustness of the prediction approach. The obtained results show that artificial neural networks with TensorFlow and Keras APIs are a relevant tool for reliability and maintenance cost prediction.