Contributions to Predict the Malfunction Probability of the Human-Machine-Environment System, Using Artificial Neural Networks
This paper presents the application of Artificial Neural Networks to predict the malfunction probability of the human-machine-environment system, in order to provide some guidance to designers of manufacturing processes. Artificial Neural Networks excel in gathering difficult non-linear relationships between the inputs and outputs of a system. We used, in this work, a feed forward neural network in order to predict the malfunction probability. The neural network is simulated with Matlab. The design experiment presented in this paper was realized at University of Pitesti, at the Faculty of Mechanics and Technology, Technology and Management Department.
Tom Savu, Nicolae Ionescu, Constantin Opran, Iulian Tabara, Adrian Bruja and Luige Vladareanu
D. C. Anghel and N. Belu, "Contributions to Predict the Malfunction Probability of the Human-Machine-Environment System, Using Artificial Neural Networks", Applied Mechanics and Materials, Vol. 760, pp. 771-776, 2015