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Abstract

Reliability-centered maintenance for production assets is a well-established concept for the most effective and efficient disposition of maintenance resources. Unfortunately, the approach takes a lot of effort and relies heavily on the knowledge of individuals. Reliability data in Computerized Maintenance Management System (CMMS) is scarce and almost never used well. An automated risk assessment system would have the potential to contribute to the dissemination and effective use of risk information and analysis. The individuality of production setting, however, prevents current systems from being practically relevant for most industries. The presented approach combines ontologies to store and link knowledge, an information logistics model displaying the various information streams, and the Internet of production to take the different user systems and infrastructure layers into account. The provided model of a reference digital shadow for risk information and a detailed information logistics model will help software companies to improve reliability software, standardize and enable assets owners to establish a customized digital shadow for their production networks.

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References

  1. Wireman, T.: Benchmarking Best Practices in Maintenance, Reliability and Asset Management: Updated for ISO 55000, 3rd edn. Industrial Press, South Norwalk (2015)

    Google Scholar 

  2. Nowlan, F.S., Heap, H.: Reliability-Centred Maintenance. Technical Information Service, US Department of Commerce, San Francisco (1978)

    Google Scholar 

  3. Bloom, N.B.: Reliability Centered Maintenance (RCM). McGraw-Hill Professional Publishing, Blacklick (2005)

    Google Scholar 

  4. Ni, H., Chen, A., Chen, N.: Some extensions on risk matrix approach. Saf. Sci. 48(10), 1269–1278 (2010). https://doi.org/10.1016/j.ssci.2010.04.005

    Article  Google Scholar 

  5. Pollanz, M.: Konzeptionelle Überlegungen zur Einrichtung und Prüfung eines Risikomanagementsystems: droht eine Mega-Erwartungslücke? Der Betrieb(52), 393–399 (1999)

    Google Scholar 

  6. Leidinger, B.: Wertorientierte Instandhaltung_ Kosten senken, Verfügbarkeit erhalten-Springer Fachmedien Wiesbaden (2017), Wertorientierte Instandhaltung: Kosten senken, Verfügbarkeit erhalten. Springer, Wiesbaden (2017). https://doi.org/10.1007/978-3-658-04401-5

  7. Al-Najjar, B.: A model to diagnose the deviation in the maintenance performance measures. In: Mathew, J. (ed.) Engineering Assessment Management: Proceedings of the 1st World Congress on Engineering Asset Management (WCEAM) 2006 Gold Coast, Queensland, Australia, 11–14 July 2006, vol. 23, pp. 87–93 Springer, London (2006). https://doi.org/10.1007/978-1-84628-814-2_8

  8. Porter, M.E.: Competitive Advantage: Creating and Sustaining Superior Performance; with a New Introduction. Free Press, New York (1998)

    Book  Google Scholar 

  9. Allee, V.: Reconfiguring the value network. J. Bus. Strategy 21(4), 36–39 (2000). https://doi.org/10.1108/eb040103

    Article  Google Scholar 

  10. British Standards Institution: Asset management: Part 1: Specification for the optimized management of physical assets 03.100.01(55-1) (2008). http://www.irantpm.ir/wp-content/uploads/2014/01/pass55-2008.pdf. Accessed 17 Dec 2019

  11. Tupa, J., Simota, J., Steiner, F.: Aspects of risk management implementation for industry 4.0. Procedia Manuf. 11, 1223–1230 (2017). https://doi.org/10.1016/j.promfg.2017.07.248

    Article  Google Scholar 

  12. Geldermann, J., Merz, M., Bertsch, V., et al.: The reference installation approach for the estimation of industrial assets at risk. EJIE 2(1), 73 (2008). https://doi.org/10.1504/EJIE.2008.016330

    Article  Google Scholar 

  13. Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica 47(2), 263–291 (1979)

    Article  MathSciNet  Google Scholar 

  14. Green, C.H., Parker, D.J., Tunstall, S.: Assessment of flood control and management options: WCD Thematic Review (2000)

    Google Scholar 

  15. Baybutt, P.: Using risk tolerance criteria to determine safety integrity levels for safety instrumented functions. J. Loss Prev. Process Ind. 25(6), 1000–1009 (2012). https://doi.org/10.1016/j.jlp.2012.05.016

    Article  Google Scholar 

  16. Gleißner, W.: Quantifizierung komplexer Risiken – Fallbeispiel Projektrisiken. Risiko-Manager (22), 7–10 (2014)

    Google Scholar 

  17. Eruguz, A.S., Tan, T., van Houtum, G.-J.: A survey of maintenance and service logistics management: classification and research agenda from a maritime sector perspective. Comput. Oper. Res. 85, 184–205 (2017). https://doi.org/10.1016/j.cor.2017.03.003

    Article  MathSciNet  MATH  Google Scholar 

  18. Murè, S., Demichela, M.: Fuzzy Application Procedure (FAP) for the risk assessment of occupational accidents. J. Loss Prev. Process Ind. 22(5), 593–599 (2009). https://doi.org/10.1016/j.jlp.2009.05.007

    Article  Google Scholar 

  19. Romeike, F.: Risikomanagement. Studienwissen kompakt. Springer, Wiesbaden (2018)

    Google Scholar 

  20. Oleinik, A.: What are neural networks not good at? On artificial creativity. Big Data Soc. 6(1), 205395171983943 (2019). https://doi.org/10.1177/2053951719839433

    Article  Google Scholar 

  21. Popov, G., Lyon, B.K., Hollcroft, B. (eds.): Risk Assessment: A Practical Guide to Assessing Operational Risks. Wiley, Hoboken (2016)

    Google Scholar 

  22. König, R.: Management betrieblicher Risiken bei produzierenden Unternehmen. Dissertation, Rheinisch-Westfälischen Technischen Hochschule, Aachen (2008)

    Google Scholar 

  23. Carpitella, S., Certa, A., Izquierdo, J., et al.: A combined multi-criteria approach to support FMECA analyses: a real-world case. Reliab. Eng. Syst. Saf. 169, 394–402 (2018). https://doi.org/10.1016/j.ress.2017.09.017

    Article  Google Scholar 

  24. Filho, S.Á., et al.: Management tool for reliability analysis in socio-technical systems - a case study. In: Boring, R.L. (ed.) AHFE 2019. AISC, vol. 956, pp. 13–25. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-20037-4_2

    Chapter  Google Scholar 

  25. Cem Kuzu, A., Akyuz, E., Arslan, O.: Application of Fuzzy Fault Tree Analysis (FFTA) to maritime industry: a risk analysing of ship mooring operation. Ocean Eng. 179, 128–134 (2019). https://doi.org/10.1016/j.oceaneng.2019.03.029

    Article  Google Scholar 

  26. Resteanu, C., Vaduva, I., Andreica, M.: Monte Carlo simulation for reliability centered maintenance management. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds.) LSSC 2007. LNCS, vol. 4818, pp. 148–156. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78827-0_15

    Chapter  Google Scholar 

  27. Si, S.-L., You, X.-Y., Liu, H.-C. et al.: DEMATEL technique: a systematic review of the state-of-the-art literature on methodologies and applications. Math. Probl. Eng. 2018(1), 1–33 (2018). https://doi.org/10.1155/2018/3696457

  28. Garg, A., Deshmukh, S.G.: Maintenance management: literature review and directions. J. Qual. Maint. Eng 12(3), 205–238 (2006). https://doi.org/10.1108/13552510610685075

    Article  Google Scholar 

  29. Karl, F.: Bedarfsermittlung und Planung von Rekonfigurationen an Betriebsmitteln. Zugl.: München, Techn. Univ., Diss., 2014. Forschungsberichte IWB/ Institut für Werkzeugmaschinen und Betriebswissenschaften, Technische Universität München, vol. 298, Utz, München (2015)

    Google Scholar 

  30. Stuckenschmidt, H.: Ontologien: Konzepte, Technologien und Anwendungen, 2. Aufl. Informatik im Fokus. Springer, Berlin (2011)

    Google Scholar 

  31. Krcmar, H.: Einführung in das Informationsmanagement, 2., überarb. Aufl. Springer Gabler, Berlin (2015)

    Google Scholar 

  32. Milvich, M.: Ein Semantisches Web für die Universitätsbibliothek Heidelberg. Masterthesis, Fachhochschule Karlsruhe (2005)

    Google Scholar 

  33. Nienke, S.: Ontologie für Energieinformationssysteme produzierender Unternehmen. Dissertation, 1. Auflage. Edition Wissenschaft Apprimus, Band 156. Apprimus Verlag, Aachen (2018)

    Google Scholar 

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Defèr, F., Schuh, G., Stich, V. (2020). Towards a Unified Reliability-Centered Information Logistics Model for Production Assets. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. The Path to Digital Transformation and Innovation of Production Management Systems. APMS 2020. IFIP Advances in Information and Communication Technology, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-030-57993-7_2

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  • DOI: https://doi.org/10.1007/978-3-030-57993-7_2

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