Prediction of Life Expectancy of Electronic Components Estimated by Neural Network

This paper presents a study on the use of neural networks (NN) for predicting the life expectancy of electronic components. Electronic components are prone to failure over time due to aging, environmental factors, and other causes. Accurate prediction of the remaining useful life of these components is critical for improving reliability and reducing downtime. In this study, we propose a neural network-based approach for predicting the life expectancy of electronic components. The neural network is trained on a dataset of historical component data and corresponding failure times. The results demonstrate that the proposed approach can accurately predict the remaining useful life of electronic components with high accuracy, outperforming traditional statistical methods. This study provides a valuable contribution to the field of prognostics and health management and has important implications for improving the reliability of electronic systems.