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Criticality analysis of a production facility using cost importance measures

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Abstract

When the estimated plant performance is inadequate, it is necessary to use appropriate methodologies and tools for production performance improvement with the minimum effort and cost in the design and/or operation phase. Hence, the concept of importance measure can be used for this purpose. It can be used to determine which components can be improved first in order to get the largest improvement in system performance. Within the system RAM (reliability, availability and maintainability) analysis, the Birnbaum importance analysis plays an important role in the performance improvement program. When both the components’ reliability and maintainability factors are considered in the importance measure analysis, it is noted that the component/system Mean Time to Repair (MTTR) is too short compared with component/system MTTR. Thus, it is necessary to bring the cost factors into the importance measure. This paper proposes a cost importance measure which considers both the reliability and the maintainability information of a system. Then, this cost importance measure is studied in a simple oil and gas production system.

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References

  1. Andrews JD, Beeson S (2003) Birnbaum’s measures of component importance for noncoherent systems analysis. IEEE Trans Reliab 52(2):213–219

    Article  Google Scholar 

  2. Aven T (1986) On the computation of certain measures of importance of system components. Microelect Reliab 26(2): 279–281

    Article  Google Scholar 

  3. Barabady J, Kumar U (2007) Availability allocation through importance measures. Inter J Qual Reliab Manage 24(6): 643–656

    Article  Google Scholar 

  4. Barlow RE, Proschan F (1975a) Importance of system components and Fault Tree events. Stochas Process App 3(1): 153–173

    Article  MATH  MathSciNet  Google Scholar 

  5. Barlow RE, Proschan F (1975b) Statistical theory of reliability and life testing: probability models. New York: Holt, Rinehart and Winston

    Google Scholar 

  6. Birnbaum ZW (1969) On the importance of different components in a multi-component system. Multivariate Analysis II, in P. R. Krishnaiah, ed., New York, Academic Press: pp 581–592

    Google Scholar 

  7. Birolini A (2007) Reliability engineering theory and practice, ISBN 978-3-540-49388-4, 5th ed. New York: Springer Berlin Heidelberg

    Google Scholar 

  8. Boland PJ, El-Neweihi E (1995) Measures of component importance in reliability theory. Compu Oper Res 22(4): 455–463

    Article  MATH  Google Scholar 

  9. Borgonovo E, Apostolakis GE (2001) A new importance measure for risk-informed decision making. Reliab Eng Syst Safety 72:193–212

    Article  Google Scholar 

  10. Cassady RC, Pohl EA, Song J (2004) Managing availability improvement efforts with importance measures and optimization. IMA J Manage Math 15(2):161–174

    Article  MATH  Google Scholar 

  11. Cheok MC, Parry GW, Sherry RS (1998) Use of importance measures in risk-informed regulatory applications. Reliab Eng Syst Safety 60:213–226

    Article  Google Scholar 

  12. Ebeling Charles E (1997) An introduction to reliability and maintainability engineering. Singapore: International Editions

    Google Scholar 

  13. Fussel JB, Vesely WE (1970) A time dependent methodology for fault tree evaluation. Nucl Eng Design 13:337–360

    Article  Google Scholar 

  14. Fussell JB (1975) How to hand-calculate system reliability and safety characteristics. IEEE Trans Reliab 24:169–174

    Article  Google Scholar 

  15. Gao X, Cui L, Li J (2007) Analysis for joint importance of components in a coherent system. Eur J Oper Res 182(1): 282–299

    Article  MATH  MathSciNet  Google Scholar 

  16. Gao X, Barabady J, Markeset T (2008) Design and operational maintainability importance measures — A case study. Q J Oper Res Soc India 45(3):189–208

    MATH  MathSciNet  Google Scholar 

  17. Hong JS, Lie CH (1993) Joint reliability-importance of two edges in an undirected network. IEEE Trans Reliab 42(1): 17–23

    Article  MATH  Google Scholar 

  18. Lambert HE (1975) Fault Trees for Decision Making in Systems Analysis. PhD thesis, UCRL-51829. University of California Livermore

  19. Levitin G, Podofillini L, Zio E (2003) Generalized importance measures for multi-state elements based on performance level restrictions. Reliab Eng Sys Safety 82:287–298

    Article  Google Scholar 

  20. Lu L and Jiang J (2007) Joint failure importance for noncoherent fault trees. IEEE Trans Reliab 56(3):435–443

    Article  Google Scholar 

  21. Pan Z, Tai Y (1988) Variance importance of system components by Monte Carlo. IEEE Trans Reliab 37(4):421–423

    Article  MATH  Google Scholar 

  22. Ramirez-Marquez JE, Coit DW (2005) Composite importance measures for multi-state systems with multi-state components. IEEE Trans Reliab 54(3):517–529

    Article  Google Scholar 

  23. Riederer KA, Haukaas T (2007) Cost-benefit importance vectors for performance-based structural engineering. J Struct Eng 133(7):907–915

    Article  Google Scholar 

  24. Xie M, Bergman B (1991) On a general measure of component importance. J Stat Plan Inf 29(1–2):211–220

    MATH  MathSciNet  Google Scholar 

  25. Zhang P, Huo C, Kezunovic M (2007) A novel measure of component importance considering cost for all-digital protection systems. IEEE Power Engineering Society General Meeting, 24–28 June, 2007, Tampa, FL, pp 1–6

  26. Zio E, Podofillini L (2003) Importance measures of multistate components in multi-state systems. Int J Reliab Qual Safe Eng 10(3):289–310

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Stavanger, N-4036, Stavanger, Norway

    Xueli Gao & Tore Markeset

  2. University of Tromsø, N-9037, Tromsø, Norway

    Javad Barabady

Authors
  1. Xueli Gao
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  2. Javad Barabady
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  3. Tore Markeset
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Correspondence to Xueli Gao.

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Gao, X., Barabady, J. & Markeset, T. Criticality analysis of a production facility using cost importance measures. Int J Syst Assur Eng Manag 1, 17–23 (2010). https://doi.org/10.1007/s13198-010-0002-0

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  • DOI: https://doi.org/10.1007/s13198-010-0002-0

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