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

Young B. Moon, C. Kenneth Divers, Hyune Ju Kim

Research output: Contribution to journalArticle

6 Scopus citations

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 languageEnglish (US)
Pages (from-to)101-108
Number of pages8
JournalComputers in Industry
Volume35
Issue number2
DOIs
StatePublished - Mar 1998

Keywords

  • Automatic early warning system (AEWS)
  • Neural networks
  • Reliability predictions

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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