Premium
Bayesian belief nets for managing expert judgement and modelling reliability
Author(s) -
Sigurdsson J. H.,
Walls L. A.,
Quigley J. L.
Publication year - 2001
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.410
Subject(s) - reliability (semiconductor) , bayesian network , variety (cybernetics) , reliability engineering , computer science , block (permutation group theory) , expert system , judgement , fault tree analysis , process (computing) , engineering , artificial intelligence , mathematics , power (physics) , physics , geometry , quantum mechanics , law , political science , operating system
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a firm mathematical background in probability theory and have been used in a variety of application areas, including reliability. BBNs can provide alternative representations of fault trees and reliability block diagrams. BBNs can be used to incorporate expert judgement formally into the modelling process. It has been claimed BBNs may overcome some of the limitations of standard reliability techniques. This paper presents an overview of BBNs and illustrates their use through a simple tutorial on system reliability modelling. The use of BBNs in reliability to date is reviewed. The challenge of using BBNs in reliability practice is explored and areas of research are identified. Copyright © 2001 John Wiley & Sons, Ltd.