@article{MTMT:1021385,
	title = {ARTIFICIAL NEURAL NETWORKS IN INTELLIGENT MANUFACTURING},
	url = {https://m2.mtmt.hu/api/publication/1021385},
	author = {Monostori, László and Barschdorff, D},
	journal-iso = {ROBOT CIM-INT MANUF},
	journal = {ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING},
	volume = {9},
	unique-id = {1021385},
	issn = {0736-5845},
	abstract = {In intelligent manufacturing systems, unprecedented, unforeseen situations and problems are expected to be solved (within certain limits) even on the basis of incomplete and imprecise information. This goal seems to be realizable only gradually, through partial solutions integrated into today's flexible manufacturing systems. The majority of artificial intelligence (AI) applications in manufacturing rely on symbolic knowledge representation and processing. This paper draws attention to another approach, namely artificial neural networks or connectionist systems, which have the ability to integrate multiple sensor information, function in real-time, possess effective knowledge representation and can learn or adapt. For the sake of completeness a short survey of different artificial neural network structures and learning algorithms is also given, together with common applications of neural network techniques in fields different from intelligent manufacturing. The most popular back propagation learning procedure, with its most important acceleration techniques, and the competitive learning approach, which has good prospects in future applications, are highlighted. This paper surveys the known neural network applications and perspectives in intelligent manufacturing. Special emphasis is given to intelligent machining, particularly in the following fields: multisensor fusion and integration, learning of process models, adaptive control, monitoring, diagnostics and quality control. Together with the results of researchers who sent papers to this survey, the authors' own investigations and contributions are illustrated. At the end of the paper a short comparison of the symbolic and connectionist approaches is given. The development and application of hybrid systems is suggested, combining the benefits of both techniques.},
	year = {1992},
	eissn = {1879-2537},
	pages = {421-437},
	orcid-numbers = {Monostori, László/0000-0001-8692-8640}
}