Prediction of Time Between Failure and Down Time of an Assembly Line With Artifical Neural Networks and Comparison of Their Results with Monte-Carlo Simulation Method Results

摘要

For frequent years, researchers apply linear methods for prediction of time series. Generally, these methods have shown in-efficiency in prediction of time series. So they are interested in using Non-linear methods of prediction. One of these Non-linear methods is Artifical Neural Networks (ANN) method. In this paper, we attempt to apply two types of neural networks, MLP and RBF networks, for prediction of Time Between Failure (TBF) and Down Time (DT) of an assembly line and compare their results with Monte-Carlo simulation method.