INDUSTRIAL AND REAL WORLD APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS Illusion or reality?

Inspired from biological nervous systems and brain structure, Artificial Neural Networks (ANN) could be seen as information processing systems, which allow elaboration of many original techniques covering a large field of applications. Among their most appealing properties, one can quote their learning and generalization capabilities. If a large number of works have concerned theoretical and implementation aspects of ANN, only a few are available with reference to their real world industrial application capabilities. In fact, applicability of an available academic solution in industrial environment requires additional conditions due to industrial specificities, which could sometimes appear antagonistic with theoretical (academic) considerations. The main goal of this paper is to present, through some of main ANN models and based techniques, their real application capability in real industrial dilemmas. Several examples dealing with industrial and real world applications have been presented and discussed covering “intelligent adaptive control”, “fault detection and diagnosis”, “decision support”, “complex systems identification” and “image processing”.