Title :
Artificial neural networks in manufacturing: concepts, applications, and perspectives
Author :
Huang, Samuel H. ; Zhang, Hong-Chao
Author_Institution :
Dept. of Ind. Eng., Texas Tech. Univ., Lubbock, TX, USA
fDate :
6/1/1994 12:00:00 AM
Abstract :
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
Keywords :
learning (artificial intelligence); manufacturing computer control; neural nets; production control; adapting; artificial neural networks; intelligent manufacturing; learning; manufacturing environment; parallel distributed computation; robustness; Artificial neural networks; Computer aided manufacturing; Computer networks; Concurrent computing; Distributed computing; Explosions; Guidelines; Intelligent manufacturing systems; Pulp manufacturing; Robustness;
Journal_Title :
Components, Packaging, and Manufacturing Technology, Part A, IEEE Transactions on