Abstract
Classical reliability methods require a crisp definition of system failure according to some performance measure that is of interest to an analyst. Therefore, they do not consider any form of uncertainty in the system failure. This limitation might result in reliability assessments that are not realistic. The uncertainty associated with qualifying the performance of the system as inadequate, i.e., failed, should be considered in reliability assessment. The objective of this contribution is to generalize currently used reliability assessment methods by treating failure as a fuzzy event. Therefore, the reliability of the system can be provided over a nonperformance spectrum. Monte Carlo simulation with variance reduction techniques will be used in the computation of the reliability.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alvi I.A.and Ayyub B.M. (1990) “Analysis of System Performance Under Stochastic and Fuzzy Uncertainty,” North American Fuzzy Information Processing Society, NAFIPS 1990, University of Toronto.
Ayyub B.M., Gupta M.M. and Kanal L.N. (1992) Analysis and Management of Uncertainty: Theory and Applications, Elsevier Science Publishing Company, Inc., New York.
Ayyub B.M. and Haldar A. (1984) “Practical Structural Reliability Techniques,” Journal of Structural Engineering, ASCE, Vol. 110, No. 8, August 1984, pp. 1707–1724.
Ayyub B.M. and Lai K-L. (1989) “Structural Reliability Assessment Using Latin Hypercube Sampling,” the proceedings of the Fifth International Conference on Structural Safety and Reliability, ICOSSAR, Volume 2, published by ASCE, Edited by A. H-S. Ang, M. Shinozuka and G. I. Schueller, San Francisco, pp. 1177–1184.
Bourgund U. and Bucher C.G. (1986) Importance Sampling Procedures Using Design Points (ISUDP)–A User Manual, Report No. 8–86, Institute of Engineering Mechanics, University of Innsbruck, Austria.
Haldar A. and Ayyub B.M. (1984) “Practical Variance Reduction Techniques in Simulation,” Publication PVP-Vol. 93, ASME, June 1984, pp. 63–74.
Harbitz A. (1986) “An Efficient Sampling Method for Probability of Failure Calculation,” Structural Safety, Vol. 3, No. 2, pp. 100–115.
Law A.M. and Kelton W.D. (1982) Simulation Modeling and Analysis, McGraw Hill Book Co., Now York.
Melchers R.E. (1987) Structural Reliability Analysis and Prediction, Ellis Horwood Limited, UK.
Rubinstein R.Y. (1981) Simulation and Monte Carlo Method, John Wiley and Sons, New York.
Schueller G.I. and Stix R. (1986) “A Critical Appraisal of Methods to Determine Failure Probabilities,” Berichtl Report 4–86, Institute of Engineering Mechanics and Institute of Mathematics, University of Innsbruck, Austria.
White G.J. and Ayyub B.M. (1985) “Reliability Methods for Ship Structures,” Naval Engineers Journal, ASNE, Vol. 97, No. 4, May 1985, pp. 86–96.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1995 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lai, KL., Ayyub, B.M. (1995). Reliability Assessment Using Variance Reduction Techniques Based on Fuzzy System Performance. In: Onisawa, T., Kacprzyk, J. (eds) Reliability and Safety Analyses under Fuzziness. Studies in Fuzziness, vol 4. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1898-7_23
Download citation
DOI: https://doi.org/10.1007/978-3-7908-1898-7_23
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-662-12913-5
Online ISBN: 978-3-7908-1898-7
eBook Packages: Springer Book Archive