AEWS: an integrated knowledge-based system with neural networks for reliability prediction

被引:4
|
作者
Moon, YB [1 ]
Divers, CK
Kim, HJ
机构
[1] Syracuse Univ, Dept Mech Aerosp & Mfg Engn, Syracuse, NY 13244 USA
[2] United Technol Carrier, Syracuse, NY 13221 USA
[3] Syracuse Univ, Dept Math, Syracuse, NY 13244 USA
关键词
automatic early warning system (AEWS); neural networks; reliability predictions;
D O I
10.1016/S0166-3615(97)00076-6
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The ability of accurately predicting reliability for products is an invaluable asset for any manufacturing company. The United Technologies Carrier developed such a system based on Weibull distribution. However, predicting accurate reliability requires experienced person's special knowledge. Two expert systems were developed to capture such knowledge. The use of Weibull plots was critical in interpreting the results of failure rates. This interpretation process was imitated by employing multi-layer feed-forward neural networks. The expert systems and neural networks are integrated with the already existing Early Warning System (EWS) and databases. The resulting system, Automatic Early Warning System (AEWS), is currently deployed in United Technologies Carrier and has led to a significant boost in productivity by at least 8 times in terms of process time. (C) 1998 Published by Elsevier Science Ltd.
引用
收藏
页码:101 / 108
页数:8
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