Advertisement

Delay Time Models Implementation Issues

  • Sylwia Werbińska-WojciechowskaEmail author
Chapter
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Abstract

This chapter is focused on a problem of developed maintenance models implementation for real-life technical systems implementation. First, there are investigated the issues of models’ parameters estimation process and its uncertainty. The conducted analysis bases on simulation modelling use and is focused on economic and reliability consequences of improper selection/estimation of modelling parameters. Later, the research analysis focused on analytical delay-time models (given in Sect.  5.2) and regards to, among others, definition of simple decision rules for the best inspection period determining. In the next section the author presents a simple methodology of applying delay-time analysis to a maintenance and inspection department. The defined algorithm is aimed at estimation of optimal inspection interval basing on the DT models developed in Chap.  5 and results obtained from the modelling parameters estimation analysis. Finally, two case studies are proposed to investigate the optimal inspection interval for two-unit systems performing in series and parallel structures. The models used to analyse the given systems are based on the results of Chap.  5 and Sect. 6.2. The first example regards to engine equipment maintenance (v-ribbed belt with belt tensioner), the second example presents the maintenance of left and right steering dumpers that are used in wheel loaders. In order to obtain the optimal inspection interval the author focuses on cost optimisation. The third example regards to the problem of maintenance policy selection based on the available operational and maintenance data from a company.

References

  1. 1.
    Bojda K, Dziaduch I, Nowakowski T, Werbinska-Wojciechowska S (2014) Decision support system for means of transport maintenance processes performance: a case study of rail buses. In: Safety, reliability and risk analysis: beyond the horizon: proceedings of the European safety and reliability conference, ESREL 2013, Amsterdam, The Netherlands, 29 Sep–2 Oct 2013. CRC Press/Balkema, Leiden, pp 909–919CrossRefGoogle Scholar
  2. 2.
    Bojda K, Werbinska-Wojciechowska S (2012) Data accessibility problem in transportation means’ maintenance performance. In: Stachowiak A (ed) Transport—strategical and operational issues: monograph. Publ. House of Poznan University of Technology, Poznan, pp 69–87Google Scholar
  3. 3.
    BS EN ISO 14224:2016 (2016) Petroleum, petrochemical and natural gas industries—collection and exchange of reliability and maintenance data for equipment (ISO 14224:2016). The Standards Policy and Strategy Committee, UKGoogle Scholar
  4. 4.
    Chlebus M, Werbinska-Wojciechowska S (2017) Assessment methods of production processes reliability: state of the art. J KONBiN 41(1):247–261CrossRefGoogle Scholar
  5. 5.
    Christer AH, Redmond DF (1992) Revising models of maintenance and inspection. Int J Prod Econ 24:227–234CrossRefGoogle Scholar
  6. 6.
    CIBSE GUIDE: Maintenance engineering and management (2008) LondonGoogle Scholar
  7. 7.
    Colson A, Cooke R (2017) Validating expert judgments and the classical model. Presentation given at TU Delft COST meeting, 4 July 2017Google Scholar
  8. 8.
    Colson A, Cooke R (2017) Cross validation for the classical model of structured expert judgment. Reliab Eng Syst Saf 163:109–120.  https://doi.org/10.1016/j.ress.2017.02.003CrossRefGoogle Scholar
  9. 9.
    Cooke RM, Goossens L (2008) TU Delft expert judgment data base. Reliab Eng Syst Saf 93:657–674.  https://doi.org/10.1016/j.ress.2007.03.005CrossRefGoogle Scholar
  10. 10.
    Cui X (2002) Delay time modeling and software development. PhD thesis, University of Salford, SalfordGoogle Scholar
  11. 11.
    Cunningham A, Wang W, Zio E, Allanson D, Wall A, Wang J (2011) Application of delay-time analysis via Monte Carlo simulation. J Mar Eng Technol 10(3):57–72.  https://doi.org/10.1080/20464177.2011.11020252CrossRefGoogle Scholar
  12. 12.
    Dabrowski T, Bednarek M (2012) Reliability of threshold-comparative diagnosis processes (in Polish). In: Proceedings of XL winter school on reliability—dependability of processes and technical systems, Publishing House of Institute for Sustainable Technologies, Radom, pp 1–23Google Scholar
  13. 13.
    Jodejko-Pietruczuk A, Werbinska-Wojciechowska S (2017) Development and sensitivity analysis of a technical object inspection model based on the delay-time concept use. Eksploat Niezawodn Maint Reliab 19(3):403–412.  https://doi.org/10.17531/ein.2017.3.11CrossRefGoogle Scholar
  14. 14.
    Jodejko-Pietruczuk A, Werbinska-Wojciechowska S (2017) Block inspection policy model with imperfect maintenance for single-unit systems. Procedia Eng 187:570–581.  https://doi.org/10.1016/j.proeng.2017.04.416CrossRefGoogle Scholar
  15. 15.
    Jodejko-Pietruczuk A, Werbinska-Wojciechowska S (2016) Influence of data uncertainty on the optimum inspection period in a multi-unit system maintained according to the block inspection policy. In: Dependability engineering and complex systems: proceedings of the eleventh international conference on dependability and complex systems DepCoS-RELCOMEX, Brunów, Poland, 27 June–1 July 2016. Springer, pp 239–256Google Scholar
  16. 16.
    Jodejko-Pietruczuk A, Werbinska-Wojciechowska S (2014) Analysis of maintenance models’ parameters estimation for technical systems with delay time. Eksploat Niezawodn Maint Reliab 16(2):288–294Google Scholar
  17. 17.
    Jones B, Jenkinson I, Wang J (2009) Methodology of using delay-time analysis for a manufacturing industry. Reliab Eng Syst Saf 94:111–124.  https://doi.org/10.1016/j.ress.2007.12.005CrossRefGoogle Scholar
  18. 18.
    Migdalski J (1982) Reliability guide—mathematical foundations (in Polish). WEMA Publ. House, WarsawGoogle Scholar
  19. 19.
    Nowakowski T (1999) Methodology for reliability prediction of mechanical objects (in Polish). Research work of the Institute of Machine Designing and Operation, Wroclaw University of Technology, WroclawGoogle Scholar
  20. 20.
    Nowakowski T, Werbinska-Wojciechowska S (2014) Data gathering problem in decision support system for means of transport maintenance processes performance development. In: Safety, reliability and risk analysis: beyond the horizon: proceedings of the European safety and reliability conference, ESREL 2013, Amsterdam, The Netherlands, 29 Sep–2 Oct 2013. CRC Press/Balkema, Leiden, pp 899–907CrossRefGoogle Scholar
  21. 21.
    Nowakowski T, Werbinska-Wojciechowska S (2013) Computer decision support system in means of transport maintenance processes performance (in Polish). In: Critical infrastructures dependability. Proceedings of conference XLI winter school of reliability, Szczyrk, 6–12 Jan 2013. Institute of Exploitation Technology Publ. House, RadomGoogle Scholar
  22. 22.
    Nowakowski T, Werbinska-Wojciechowska S (2012) Means of transport maintenance processes performance: decision support system. In: Proceedings of Carpathian logistics congress CLC’ 2012, Jesenik, Czech Republic, 7–9 Nov 2012. Tanger, Ostrava, pp 1–6Google Scholar
  23. 23.
    Nowakowski T, Werbinska-Wojciechowska S (2012) Uncertainty problem in decision support system for means of transport maintenance processes performance development. J KONBiN 3:173–192CrossRefGoogle Scholar
  24. 24.
    Nowakowski T, Werbinska S (2009) On problems of multi-component system maintenance modelling. Int J Autom Comput 6(4):364–378CrossRefGoogle Scholar
  25. 25.
    Pillay A, Wang J, Wall AD (2001) A maintenance study of fishing vessel equipment using delay-time analysis. J Qual Maint Eng 7(2):118–127CrossRefGoogle Scholar
  26. 26.
    PN-EN 60300-3-1:2005 (2005) Dependability management—part 3-1: application guide—analysis techniques for dependability—guide on methodology. The Polish Committee for Standardization, WarsawGoogle Scholar
  27. 27.
    Scarf PA (2007) A framework for condition monitoring and condition based maintenance. Qual Technol Quant Manag 4(2):301–312.  https://doi.org/10.1080/16843703.2007.11673152MathSciNetCrossRefGoogle Scholar
  28. 28.
    Wang W (2002) A delay time based approach for risk analysis of maintenance activities. Saf Reliab 23(1):103–113.  https://doi.org/10.1080/09617353.2002.11690753MathSciNetCrossRefGoogle Scholar
  29. 29.
    Wang W, Christer AH (2003) Solution algorithms for a nonhomogeneous multi-component inspection model. Comput Oper Res 30:19–34.  https://doi.org/10.1016/S0305-0548(01)00074-0MathSciNetCrossRefzbMATHGoogle Scholar
  30. 30.
    Wen-Yuan Lv, Wang W (2006) Modelling preventive maintenance of production plant given estimated PM data and actual failure times. In: Proceedings of international conference on management science and engineering, 2006 ICMSE’06, IEEE, pp 387–390.  https://doi.org/10.1109/icmse.2006.313857
  31. 31.
    Werbinska-Wojciechowska S, Zajac P (2015) Use of delay-time concept in modelling process of technical and logistics systems maintenance performance. Case study. Eksploat Niezawodn Maint Reliab 17(2):174–185CrossRefGoogle Scholar
  32. 32.
    Werner C, Bedford T, Cooke R, Hanea A (2017) Expert judgement for dependence in probabilistic modelling: a systematic literature review and future research directions. Eur J Oper Res 258:801–819.  https://doi.org/10.1016/j.ejor.2016.10.018MathSciNetCrossRefzbMATHGoogle Scholar
  33. 33.
    Wilson KJ (2017) An investigation of dependence in expert judgment studies with multiple experts. Int J Forecast 33:325–336.  https://doi.org/10.1016/j.ejor.2016.10.018CrossRefGoogle Scholar
  34. 34.
    Zhang Y, Andrews J, Reed S, Karlberg M (2017) Maintenance processes modelling and optimisation. Reliab Eng Syst Saf 168:150–160.  https://doi.org/10.1016/j.ress.2017.02.011CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Wroclaw University of Science and TechnologyWroclawPoland

Personalised recommendations