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Failure Effects Analysis by Multiple Random Variable

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Smart Solutions in Today’s Transport (TST 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 715))

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Abstract

The safety-related systems are typically resisting against dangerous faults. Failure effects on the system can be determined directly by monitoring the original system installation, by simulation of the system operation using its model, or by computing or theoretical reasoning. The process of system ageing can be described with the help of the random failure time. If the system contains \( n \) elements, generally, the ageing process can be characterised as the \( n \)-dimensional random process with time-dependent random variables of the \( n \)-dimensional random vector. The probability density of the failure occurrence of the \( i \)-th system element is represented by the i-th random variable of the random vector. If the analysis of the safety integrity of the safety-related electronic system is used method FTA, that application of knowledge in the field of multiple random variable can greatly simplify the computation of dangerous failure (top event) rate.

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References

  1. Einer, S., Slovák, R., Schnieder, E.: Modelling train systems with Petri nets—an operational specification. In: 2000 IEEE International Conference on Systems, Man, and Cybernetics, vol. 5, 8–11 October 2000, pp. 3207–3211 (2000)

    Google Scholar 

  2. Guo, L.J., Kang, J.X.: An extended HAZOP analysis approach with dynamic fault tree. J. Loss Prev. Process Ind. 38, 224–232 (2015)

    Article  Google Scholar 

  3. Klavner, A., Volovoj, V.: Application of Petri nets to reliability prediction of occupant safety systems with partial detection and repair. Reliab. Eng. Syst. Saf. 95, 606–613 (2010)

    Article  Google Scholar 

  4. Rástočný, K., Rástočný Jr., K.: UML—a part of an interlocking system development process. In: Mikulski, J. (ed.) TST 2012. CCIS, vol. 329, pp. 293–300. Springer, Heidelberg (2012). doi:10.1007/978-3-642-34050-5_33

    Chapter  Google Scholar 

  5. Rástočný, K., Ždánsky, J.: Hazardous failure rate of the safety function. In: Mikulski, J. (ed.) TST 2015. CCIS, vol. 531, pp. 284–291. Springer, Cham (2015). doi:10.1007/978-3-319-24577-5_28

    Chapter  Google Scholar 

  6. Rástočný, K., et al.: Quantitative assessment of safety integrity level of message transmission between safety-related equipment. J. Comput. Inform. 33, 1001–1026 (2014)

    Google Scholar 

  7. Rástočný, K., Ilavský, J.: Effects of a periodic maintenance on the safety integrity level of a control system. In: Schnieder, E., Tarnai, G. (eds.) FORMS/FORMAT 2010—Formal Methods for Automation and Safety in Railway and Automotive Systems, pp. 77–85. Springer, Berlin (2011). doi:10.1007/978-3-642-14261-1_8

    Google Scholar 

  8. Skalný, P.: An application of graph theory in Markov chains. Reliability analysis. Adv. Electr. Electron. Eng. 12(2), 154–159 (2014)

    Google Scholar 

  9. Shu, Y., Zhao, J.: A simplified Markov-based approach for safety integrity level verification. J. Loss Prev. Process Ind. 29, 262–266 (2014)

    Article  Google Scholar 

  10. Rástočný, K., et al.: Effects of diagnostic on the safety of a control system realised by safety PLC. In: 11th International Conference ELEKTRO 2016. Slovakia, 16–18 May, pp. 462–467 (2016)

    Google Scholar 

  11. http://www.bqr.com. Accessed 12 Feb 2017

  12. http://www.ptc.com/product-lifecycle-management/windchill/product-risk-and-reliability. Accessed 12 Feb 2017

  13. http://www.itemuk.com. Accessed 12 Feb 2017

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Acknowledgements

This paper has been supported by the Educational Grant Agency of the Slovak Republic (KEGA) Number 034ŽU-4/2016: Implementation of modern technologies focusing on control using the safety PLC into education (50%) and particularly by the project Number: 008ŽU-4/2015: Innovation of HW and SW tools and methods of laboratory education focused on safety aspects of ICT within safety critical applications of processes control (50%).

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Correspondence to Jozef Balák .

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Rástočný, K., Franeková, M., Balák, J. (2017). Failure Effects Analysis by Multiple Random Variable. In: Mikulski, J. (eds) Smart Solutions in Today’s Transport. TST 2017. Communications in Computer and Information Science, vol 715. Springer, Cham. https://doi.org/10.1007/978-3-319-66251-0_34

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  • DOI: https://doi.org/10.1007/978-3-319-66251-0_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66250-3

  • Online ISBN: 978-3-319-66251-0

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