Skip to main content

Identifying Significance of Human Cognition in Future Maintenance Operations

  • Conference paper
  • First Online:
Intelligent Human Systems Integration (IHSI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 722))

Included in the following conference series:

Abstract

Industrial maintenance in future will operate heavily with intelligent systems. Advanced sensor networks on machines will enable them communicate and learn about failure types, predict consequences and share solutions. Humans on the other hand are equipped with intuitive cognition that facilitates acquisition of knowledge about unique characteristics of individual machines, and use this knowledge in maintenance problem solving. In this article, we identify two major opportunities to collaborate human intuitive cognition with intelligent systems for future maintenance solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Stary, C., Neubauer, M.: Industrial challenges. In: Neubauer, M., Stary, C. (eds.) S-BPM in the Production Industry. Springer, Cham (2017)

    Google Scholar 

  2. Crowder, J.A., Carbone, J.N.: Collaborative shared awareness: Human-AI Collaboration. In: International Conference on Information and Knowledge Engineering, WorldComp, Athens, pp. 1–6 (2014)

    Google Scholar 

  3. Dhillon, B.S.: Human error in maintenance: an investigative study for the factories of the future. In: IOP Conference Series: Materials Science and Engineering, vol. 65. IOP Publishing (2014)

    Google Scholar 

  4. Pirsig, R.M.: Zen and the Art of Motorcycle Maintenance. William Morrow and Company, New York (1974)

    Google Scholar 

  5. Nonaka, I., Toyama, R., Konno, T.: SECI, Ba and leadership: a unified model of dynamic knowledge creation. Long Range Plan. 33, 5–34 (2000)

    Article  Google Scholar 

  6. Patterson, R.E., Pierce, B.J., Bell, H.H.: Implicit learning, tacit knowledge, expertise development, and naturalistic decision making. J. Cogn. Eng. Decis. Making 4(4), 289–303 (2010)

    Article  Google Scholar 

  7. Croft, D.G., Banbury, S.P., Butler, L.T., et al.: The role of awareness in situation awareness. In: Banbury, S., Tremblay, S., (eds.) A Cognitive Approach for Situation Awareness. Ashgate, Hampshire (2004)

    Google Scholar 

  8. Amadi-Echendu, J., de Smidt, M.: Integrating tacit knowledge for condition assessment of continuous mining machines. In: Amadi-Echendu, J., Hoohlo, C., Mathew, J. (eds.) 9th WCEAM Research Papers. LNME, vol. 1, pp. 119–130. Springer, Cham (2015)

    Chapter  Google Scholar 

  9. Djiksterhuis, A., Nordgren, L.F.: A theory of unconscious thought. Perspect. Psycholog. Sci. 1, 95–106 (2006)

    Article  Google Scholar 

  10. Sagiv, N., Ilbeigi, A., Ben-tal, O.: Reflections on synaesthesia, perception and cognition. Intellectica. 55, 81–94 (2011)

    Google Scholar 

  11. UK Synaesthesia Association. http://www.uksynaesthesia.com

  12. Simner, J.: Defining synaesthesia: a response to two excellent commentaries. Br. J. Psychol. 103, 24–27 (2012)

    Article  Google Scholar 

  13. Silver, D., Schrittwieser, J., Simonyan, K., et al.: Mastering the game of go without human knowledge. Nature 550, 354–359 (2017)

    Article  Google Scholar 

  14. British Go Association. www.britgo.org

  15. Nielsen, M.: How Google’s AlphaGo Imitates Human Intuition. Technology, 4 April 2016

    Google Scholar 

  16. Duanmu, J.L., Fai, F.M.: A processual analysis of knowledge transfer: from foreign MNEs to Chinese suppliers. Int. Bus. Rev. 16(4), 449–473 (2010)

    Article  Google Scholar 

  17. Refaiy, M., Labib, A.: The effect of applying tacit knowledge on maintenance performance: an empirical study of the energy sector in the UK and Arab countries. Knowl. Manag. Res. Pract. 7(3), 277–288 (2009)

    Article  Google Scholar 

  18. Klein, G.: Sources of Power: How People Make Decisions. MIT Press, Cambridge (1998)

    Google Scholar 

  19. Buckwalter, W.: Intuition fail: philosophical activity and the limits of expertise. Philos. Phenomenolog. Res. 92(2), 378–410 (2016)

    Article  Google Scholar 

  20. Dane, E., Pratt, M.G.: Exploring intuition and its role in managerial decision making. Acad. Manag. Rev. 32(1), 33–54 (2007)

    Article  Google Scholar 

  21. Gigerenzer, G.: Gut feelings: the intelligence of the unconscious. In: Järvilehto, L. (ed.) The Nature and Function of Intuitive Thought and Decision Making, Springer Briefs in Well-Being and Quality of Life Research. Springer, Heidelberg (2015)

    Google Scholar 

  22. Järvilehto, L.: The Nature and Function of Intuitive Thought and Decision Making. Springer Briefs in Well-Being and Quality of Life Research. Springer, Heidelberg (2015)

    Book  Google Scholar 

  23. Parasuraman, R., Sheridan, T.B., Wickens, C.D.: A model for types and levels of human interaction with automation. IEEE Trans. Syst. Man Cybern. 30(3), 286–297 (2000)

    Article  Google Scholar 

  24. Cummings, M.L., Bruni, S.: Collaborative human-automation decision making. In: Nof, S. (ed.) Springer Handbook of Automation. Springer, Heidelberg (2009)

    Google Scholar 

  25. Maliszewska, P., Krebs, I., Dudek, A.: An approach to automated tacit-knowledge acquisition and transformation in manufacturing companies. In: International Conference on Methods and Models in Automation and Robotics, pp. 356–360. Miedzyzdroje (2017)

    Google Scholar 

  26. Patterson, R.E.: Intuitive cognition and models of human-automation interaction. Hum. Factors 59(1), 101–115 (2017)

    Article  Google Scholar 

Download references

Acknowledgments

We acknowledge Luleå Railway Research Centre (JVTC) for funding this project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Prasanna Illankoon .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Illankoon, P., Tretten, P., Kumar, U. (2018). Identifying Significance of Human Cognition in Future Maintenance Operations. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_86

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73888-8_86

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73887-1

  • Online ISBN: 978-3-319-73888-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics