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Reliability of a Network with Heterogeneous Components Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Optimal Testing Resources Allocation for Improving Reliability Assessment of Non-repairable Multi-state Systems

Authors : Yu Liu, Tao Jiang, Peng Lin

Published in: Recent Advances in Multi-state Systems Reliability

Publisher: Springer International Publishing

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Abstract

Due to limited reliability testing resources (e.g., budget, time, and manpower etc.), the reliability of a sophisticated system may not be able to accurately estimated by insufficient reliability testing data. The book chapter explores the reliability testing resources allocation problem for multi-state systems, so as to improve the accuracy of reliability estimation of an entire system. The Bayesian reliability assessment method is used to infer the unknown parameters of multi-state components by merging subjective information and continuous/discontinuous inspection data. The performance of each candidate testing resources allocation scheme is evaluated by the proposed uncertainty quantification metrics. By introducing the surrogate model, i.e., kriging model, the computational burden in seeking the optimal testing resources allocation scheme can be greatly reduced. The effectiveness and efficiency of the proposed method are exemplified via two illustrative case.

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previous chapter Trade-Off Between Redundancy, Protection, and Imperfect False Targets in Defending Parallel Systems
next chapter Topological Analysis of Multi-state Systems Based on Direct Partial Logic Derivatives
Literature
1.
Lisnianski A, Frenkel I, Ding Y (2010) Multi-state system analysis and optimization for engineers and industrial managers. Springer, LondonCrossRefMATH
2.
Lisnianski A, Levitin G (2003) Multi-state system reliability: assessment. Optimization and applications. World Scientific, Singapore
3.
Kuo W, Zuo MJ (2003) Optimal reliability modeling: principles and applications. Wiley, Hoboken, NJ
4.
Lisnianski A, Elmakias D, Laredo D, Haim HB (2012) A multi-state Markov model for a short-term reliability analysis of a power generating unit. Reliab Eng Sys Saf 98(1):1–6CrossRef
5.
Ding Y, Zuo MJ, Lisnianski A, Tian Z (2008) Fuzzy multi-state systems: general definitions, and performance assessment. IEEE Trans Reliab 57(4):589–594CrossRef
6.
Liu Y, Huang HZ (2010) Reliability assessment for fuzzy multi-state systems. Int J Syst Sci 41(4):365–379CrossRef
7.
Li CY, Chen X, Yi XS, Tao JY (2011) Interval-valued reliability analysis of multi-state systems. IEEE Trans Reliab 60(4):595–606
8.
Destercke S, Sallak M (2013) An extension of universal generating function in multi-state systems considering epistemic uncertainties. IEEE Trans Reliab 62(2):504–514CrossRef
9.
Liu Y, Lin P, Huang HZ (2015) Bayesian reliability and performance assessment for multi-state systems. IEEE Trans Reliab 64(1):394–409CrossRef
10.
Hamada M, Martz HF, Reese CS, Graves T, Johnson V, Wilson AG (2004) A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation. Reliab Eng Sys Saf 86(3):297–305CrossRef
11.
Anderson-Cook CM, Graves TL, Hamada MS (2009) Reliability allocation for reliability of a complex system with aging components. Qual Reliab Eng Int 25:481–494CrossRef
12.
Lu L, Chapman JL, Anderson-Cook CM (2013) A case study on selecting a best allocation of new data for improving the estimation precision of system and subsystem reliability using Pareto fronts. Technometrics 55(4):473–487MathSciNetCrossRef
13.
Yu K, Koren I, Guo Y (1994) Generalized multistate monotone coherent systems. IEEE Trans Reliab 43(2):242–250CrossRef
14.
Wang P, Youn BD, Xi Z, Kloess A (2009) Bayesian reliability analysis with evolving, insufficient, and subjective data sets. J Mech Des 131(11):111008CrossRef
15.
Smith JQ (1998) Decision analysis: a Bayesian approach. Chapman and Hall, London
16.
17.
Kelly D, Smith C (2011) Bayesian inference for probabilistic risk assessment. Springer, LondonCrossRefMATH
18.
Levitin G (2005) The universal generating function in reliability analysis and optimization. Springer, London
19.
Wynn HP (2004) Maximum entropy sampling and general equivalence theory. Advances in model-oriented design and analysis, contributions to statistics. Physica-Verlag, Heidelberg, pp 211–218
20.
Jin R, Chen W, Simpson T (2001) Comparative studies of metamodeling techniques under multiple modelling criteria. Struct Multidiscip Optim 23:1–13CrossRef
21.
Jin R, Du X, Chen W (2003) The use of metamodeling techniques for optimization under uncertainty. Struct Multidiscip Optim 25:99–116CrossRef
22.
Cremona MA, Liu B, Hu Y, Bruni S, Lewis R (2016) Predicting railway wheel wear under uncertainty of wear coefficient, using universal kriging. Reliab Eng Sys Saf 154:49–59CrossRef
23.
Liu Y, Shi Y, Jiang T, Liu JZ, Wang WJ (2016) Metamodel-based direction guidance system optimization for improving efficiency of aircraft emergency evacuation. Comp Ind Eng 91:302–314CrossRef
24.
Zhang M, Gou W, Li L, Yang F, Yue Z (2016) Multidisciplinary design and multi-objective optimization on guide fins of twin-web disk using Kriging surrogate model. Struct Multidiscip Optim 55(1):361–373
25.
Jin R, Chen W, Sudjianto A (2002) On sequential sampling for global metamodeling in engineering design. In: Proceedings of ASME 2002 design engineering technical conferences and computers and information in engineering conference, Montreal, Canada, pp 539–548
26.
Wang GG, Shan S (2006) Review of metamodeling techniques in support of engineering design optimization. J Mech Des 129(4):370–380CrossRef
27.
Gen M, Yun YS (2006) Soft computing approach for reliability optimization: state-of-the-art survey. Reliab Eng Sys Saf 91(9):1008–1026CrossRef
28.
Levitin G (2006) Genetic algorithms in reliability engineering. Reliab Eng Sys Saf 91(9):975–976CrossRef
29.
Jiang T, Liu Y (2017) Parameter inference for non-repairable multi-state system reliability models by multi-level observation sequences. Reliab Eng Sys Saf 166:3–15
30.
Liu Y, Chen CJ (2017) Dynamic reliability assessment for nonrepairable multistate systems by aggregating multilevel imperfect inspection data. IEEE Trans Reliab 66(2):281–297
Metadata
Title
Optimal Testing Resources Allocation for Improving Reliability Assessment of Non-repairable Multi-state Systems
Authors
Yu Liu
Tao Jiang
Peng Lin
Copyright Year
2018
Book
Recent Advances in Multi-state Systems Reliability

Print ISBN: 978-3-319-63422-7

Electronic ISBN: 978-3-319-63423-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-63423-4_13