Abstract
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.
Original language | English (US) |
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Pages (from-to) | 101-108 |
Number of pages | 8 |
Journal | Computers in Industry |
Volume | 35 |
Issue number | 2 |
DOIs | |
State | Published - Mar 1998 |
Keywords
- Automatic early warning system (AEWS)
- Neural networks
- Reliability predictions
ASJC Scopus subject areas
- General Computer Science
- General Engineering