TY - JOUR
T1 - Applications of neural networks in manufacturing
T2 - A state-of-the-art survey
AU - Zhang, H. C.
AU - Huang, S. H.
N1 - Funding Information:
This research was supported in part by the National Science Foundation under the Grant contract # DDM-9211657.
PY - 1995/3
Y1 - 1995/3
N2 - Artificial intelligence has been claimed to yield revolutionary advances in manufacturing. While most of the survey papers about artificial intelligence in manufacturing have been focused on knowledge-based expert systems, fewer attentions have been paid to neural networks. However, neural networks are able to learn, adapt to changes, and can mimic human thought processes with little human interventions. They could be of great help for the present computer-integrated manufacturing and the future intelligent manufacturing systems. This paper presents a state-of-the-art survey of neural network applications in manufacturing. The objective of this paper is to update information about the applications of neural networks in manufacturing, which will provide some guidelines and references for the research and implementation.
AB - Artificial intelligence has been claimed to yield revolutionary advances in manufacturing. While most of the survey papers about artificial intelligence in manufacturing have been focused on knowledge-based expert systems, fewer attentions have been paid to neural networks. However, neural networks are able to learn, adapt to changes, and can mimic human thought processes with little human interventions. They could be of great help for the present computer-integrated manufacturing and the future intelligent manufacturing systems. This paper presents a state-of-the-art survey of neural network applications in manufacturing. The objective of this paper is to update information about the applications of neural networks in manufacturing, which will provide some guidelines and references for the research and implementation.
UR - http://www.scopus.com/inward/record.url?scp=0000414908&partnerID=8YFLogxK
U2 - 10.1080/00207549508930175
DO - 10.1080/00207549508930175
M3 - Article
AN - SCOPUS:0000414908
SN - 0020-7543
VL - 33
SP - 705
EP - 728
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 3
ER -