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Innovation in Medicine and Healthcare Systems, and Multimedia pp 517–527Cite as

The Industrial Internet of Things: Examining How the IIoT Will Improve the Predictive Maintenance

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 145))

Abstract

We are currently at the dawn of the fourth industrial revolution, the notions industry, smart factories, the Internet of Things (IoT), cyber-physical systems, and digital transformation often refer to the upheaval that quickly transforms the landscape of the industrial sector. Industry 4.0 includes the digitization of horizontal value chains and vertical, innovation of products and services, and the creation of new business models. Among the main operational drivers of the transformation are the improvement of the customer, speeding up marketing, and reducing costs. In this paper, the predictive maintenance represents an essential building block of the smart factory, where high availability of production facilities and minimization of downtime is an important goal. The goal of this paper is to design and analyze an efficient framework for the industrial IoT, providing a state-of-the-art approach for industrial applications. We also focus on predictive maintenance of production systems, including manufacturing machines to increase the process quality.

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References

  1. Stankovic, J.A.: Research directions for the internet of things. IEEE Internet Things J. 1(1), 3–9 (2014)

    Article  MathSciNet  Google Scholar 

  2. Khan, R., Khan, S.U., Zaheer, R., Khan, S.: Future internet: The internet of things architecture, possible applications and key challenges. In: 2012 10th International Conference on Frontiers of Information Technology (FIT), pp. 257–260 (2012)

    Google Scholar 

  3. Kagermann, H., Wahlster, W., Helbig, J: Recommendations for implementing the strategic initiative INDUSTRIE 4.0, Frankfurt/Main: Acatech National Academy of Science and Engineering (2013)

    Google Scholar 

  4. Bauernhansl, T., Hompel, M., Vogelheuser, B.: Industrie 4.0 in Produktion, Automatisierung und Logistik. Anwendung, Technologien, Migration, Wiesbaden: Springer Fachmedien, p. 634 (2014). ISBN 978-3-658-04681-1

    Google Scholar 

  5. Márquez, A.C.: The Maintenance Management Framework: Models and Methods for Complex Systems Maintenance. Springer Verlag London Limited, Sevilla, Spain (2007)

    Google Scholar 

  6. Moya, M.C.C.: The control of the setting up of a predictive maintenance programme using a system of indicators. Omega: Int. J. Manag. Sci. 32(1), 57–75 (2004). ISSN 0305-0483

    Article  Google Scholar 

  7. Lucke, D., Constantinescu, C., Westkämper, E.: Smart factory-a step towards the next generation of manufacturing. In: Manufacturing Systems and Technologies for the New Frontier, pp. 115–118. Springer, Berlin (2008)

    Google Scholar 

  8. Okoh, P., Haugen, S.: Maintenance-related major accidents: classification of causes and case study. J. Loss Prev. Process Ind. 26(6), 1060–1070 (2013)

    Article  Google Scholar 

  9. Susto, G.A., Schirru, A., Pampuri, S., McLoone, S., Beghi, A.: Machine learning for predictive maintenance: a multiple classifiers approach. IEEE Trans. Industr. Inf. 11(3), 812–820 (2015). https://doi.org/10.1109/TII.2014.2349359

    Article  Google Scholar 

  10. Chehri, A., Hussein, H.T., Farjow, W.: Indoor cooperative positioning based on fingerprinting and support vector machines. In: Akan, O. (ed.) Mobile and Ubiquitous Systems: Computing, Networking, and Services. vol. 73, pp. 114–124 (2012)

    Google Scholar 

  11. Farjow, W., Chehri, A., Mouftah, H.T., Fernando, X.: Support vector machines for indoor sensor node localization. In: Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC), pp. 779–783 (2011)

    Google Scholar 

  12. Koksal, G., Batmaz, I., Testik, M.C.: A review of data mining applications for quality improvement in manufacturing industry. Expert Syst. Appl. 38(10), 13448–13467 (2011)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Applied Sciences, University of Québec in Chicoutimi, G7H 2B1, Chicoutimi, QC, Canada

    Abdellah Chehri

  2. School of Electronic Engineering, Xidian University, 2 South Taibai Road, 710071, Xi’an, Shaanxi, China

    Gwanggil Jeon

  3. Department of Embedded Systems Engineering, Incheon National University, 119 Academy-Ro, Yeonsu-Gu, 22012, Incheon, Korea

    Gwanggil Jeon

Authors
  1. Abdellah Chehri
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  2. Gwanggil Jeon
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Corresponding author

Correspondence to Abdellah Chehri .

Editor information

Editors and Affiliations

  1. Kusuatsu, Shiga, Japan

    Yen-Wei Chen

  2. Faculty of Informatics, Reutlingen University, Reutlingen, Baden-Württemberg, Germany

    Alfred Zimmermann

  3. Shoreham-by-sea, UK

    Robert J. Howlett

  4. University of Canberra, Canberra, ACT, Australia

    Lakhmi C. Jain

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Chehri, A., Jeon, G. (2019). The Industrial Internet of Things: Examining How the IIoT Will Improve the Predictive Maintenance. In: Chen, YW., Zimmermann, A., Howlett, R., Jain, L. (eds) Innovation in Medicine and Healthcare Systems, and Multimedia. Smart Innovation, Systems and Technologies, vol 145. Springer, Singapore. https://doi.org/10.1007/978-981-13-8566-7_47

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