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Artificial neural networks in manufacturing: concepts, applications, and perspectives

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2 Author(s)
S. H. Huang ; Dept. of Ind. Eng., Texas Tech. Univ., Lubbock, TX, USA ; Hong-Chao Zhang

New approaches and techniques are continuously and rapidly introduced and adopted in today's manufacturing environment. Recently, there has been an explosion of interest in applying artificial neural networks to manufacturing. Artificial neural networks have several advantages that are desired in manufacturing practice, including learning and adapting ability, parallel distributed computation, robustness, etc. There is an expectation that neural network techniques can lead to the realization of truly intelligent manufacturing systems. This paper introduces the basic concepts of neural networks and reviews the current application of neural networks in manufacturing. The problems with neural networks are also identified and some possible solutions are suggested. The aim of the authors is to provide useful guidelines and references for the research and implementation of artificial neural networks in the field of manufacturing

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IEEE Transactions on Components, Packaging, and Manufacturing Technology: Part A  (Volume:17 ,  Issue: 2 )