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Modeling system reliability aspects of ERTMS/ETCS by fault trees and Bayesian networks
2006 (English)In: Proceedings of the European Safety and Reliability Conference 2006, ESREL 2006 - Safety and Reliability for Managing Risk, 2006, p. 2675-2683Conference paper, Published paper (Refereed)
Abstract [en]

Critical control systems require proper techniques to predict their failure rate since early design stages, in order to fulfil dependability requirements and minimize development costs. Bayesian Networks have been shown to be suitable to model system reliability aspects, extending the modeling power of Fault Trees and featuring a better solving efficiency with respect to Petri Nets. In this paper we exploit the Fault Tree and Bayesian Network formalisms in order to perform a hardware reliability analysis of a complex real world case study: the European Railway Traffic Management System/European Train Control System (ERTMS/ETCS). ERTMS/ETCS is a recent standard specification aimed at improving interoperability, performances and dependability of modern railways. An implementation of ERTMS/ETCS is a distributed heterogeneous system with strict reliability requirements. Starting from such requirements and from a reference hardware architecture, we studied system reliability by instantiating models with realistic parameters and performing a series of sensitivity analyses in order to highlight design trade-offs. By evaluating and integrating sub-models using a compositional approach we both obtained several interesting results and showed the effectiveness of a combined use of Fault Trees and Bayesian Networks in dealing with system reliability analyses of train control systems. © 2006 Taylor & Francis Group.

Place, publisher, year, edition, pages
2006. p. 2675-2683
Keywords [en]
Bayesian networks, Computer networks, Control system analysis, Control systems, Control theory, Distributed parameter networks, Failure analysis, Fault tree analysis, Graph theory, Inference engines, Intelligent networks, Knowledge based systems, Locomotives, Marine biology, Network management, Petri nets, Quality assurance, Railroad cars, Railroad traffic control, Railroad transportation, Railroads, Reliability analysis, Risk management, Sensitivity analysis, Speech analysis, Speech recognition, Forestry, Case studies, Compositional approaches, Critical control systems, Design trades, Development costs, Distributed heterogeneous systems, Early design stages, European railways, Failure rates, Fault trees, Hardware architectures, Hardware reliabilities, Model systems, Modeling powers, Modeling systems, Real worlds, Reliability requirements, System reliabilities, Train control systems, Reliability, Design tradeoff, Failure rate, Fault-trees, Hardware architecture, Hardware reliability, Heterogeneous systems, Model system, Modeling power, Submodels, System reliability
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:lnu:diva-73696Scopus ID: 2-s2.0-56149113005ISBN: 0415416205 ISBN: 9780415416207 OAI: oai:DiVA.org:lnu-73696DiVA, id: diva2:1213846
Conference
European Safety and Reliability Conference 2006, ESREL 2006 - Safety and Reliability for Managing Risk, 18 September 2006 through 22 September 2006, Estoril
Note

Conference code: 74057; Cited By :27; Export Date: 26 April 2018; Conference Paper; Correspondence Address: Flammini, F.; ANSALDO SIGNAL - Ansaldo Segnalamento Ferroviario S.p.A., Naples, Italy; References: Ajmone Marsan, M., Balbo, G., Conte, G., Donatelli, S., Franceschinis, G., (1995) Modeling with Generalized Stochastic Petri Nets, , J. Wiley; Bobbio, A., Bologna, S., Ciancamerla, E., Franceschinis, G., Gaeta, R., Minichino, M., Portinale, L., Comparison of Methodologies for the Safety and Dependability Assessment of an Industrial Programmable Logic Controller (2001) Proceedings of ESREL 2001, , Torino; Bobbio, A., Portinale, L., Minichino, M., Ciancamerla, E., Improving the Analysis of Dependable Systems by Mapping Fault Trees into Bayesian Networks (2001) Reliability Engineering and System Safety Journal, 71 (3), pp. 249-260; CENELEC 1999. EN 50126 Railways Applications - The specification and demonstration of Reliability, Maintainability and Safety (RAMS); Dugan, J.B., Bavoso, S.J., Boyd, M.A., Dynamic Fault-Tree Models for Fault Tolerant Computer Systems (1992) IEEE Transactions on Reliability, 41, pp. 363-377; Flammini, F., Iacono, M., Marrone, S., Mazzocca, N., Using Repairable Fault Trees for the evaluation of design choices for critical repairable systems (2005) Proceedings of the 9th IEEE International Symposium on High Assurance Systems Engineering, pp. 163-172. , HASE, Heidelberg, Germany, October 12-14: pp; Montani, S.; Portinale, L.; & Bobbio A. 2005. Dynamic Bayesian Networks for Modeling Advanced Fault Tree Features in Dependability Analysis. Proc. of European Safety and Reliability Conference (ESREL 2005), Tri City, Poland: pp. 1415-1422; NASA Office of Safety and Mission Assurance 2002. Fault Tree Handbook with Aerospace Applications, ver. 1.1; (2006) Netica web site, , http://www.norsys.com/netica.html; Portinale, L., Bobbio, A., Montani, S., From AI to Dependability: Using Bayesian Networks for Reliability Modeling and Analysis (2004) Proceedings of the Fourth International Conference on Mathematical Methods in Reliability (MMR2004); Sahner, R.A., Trivedi, K.S., Puliafito, A., (1996) Performance and Reliability Analysis of Computer Systems: An Example-based Approach Using the SHARPE Software Package, , Kluwer Academic Publishers; (1999) ERTMS/ETCS - RAMS Requirements Specification, , UNISIG; (2002) ERTMS/ETCS - Class1 SRS Issue 2.2.2, Subset-026, , UNISIG; Watthayu, W., A Bayesian network based framework for multi-criteria decision making (2004) Proceedings of the 17th International Conference on Multiple Criteria Decision Analysis

Available from: 2018-06-05 Created: 2018-06-05 Last updated: 2018-06-05

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