IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-319-95666-4_3.html
   My bibliography  Save this book chapter

A Proactive Model for Joint Maintenance and Logistics Optimization in the Frame of Industrial Internet of Things

In: Operational Research in the Digital Era – ICT Challenges

Author

Listed:
  • Alexandros Bousdekis

    (National Technical University of Athens (NTUA))

  • Gregoris Mentzas

    (National Technical University of Athens (NTUA))

Abstract

Equipment failures in manufacturing processes concern industries because they can lead to severe issues regarding human safety, environmental impact, reliability, and production costs. The stochastic nature of equipment degradation and the uncertainty about future breakdowns affect significantly the maintenance and inventory decisions. Proactive event processing can facilitate this decision-making process in an Industrial Internet of Things (IIoT) environment, but real-time data processing poses several challenges in efficiency and scalability of the associated information systems. Therefore, appropriate real-time, event-driven algorithms and models are required for deciding on the basis of predictions, ahead of time. We propose a proactive event-driven model for joint maintenance and logistics optimization in a sensor-based, data-rich industrial environment. The proposed model is able to be embedded in a real-time, event-driven information system in order to be triggered by prediction events about the future equipment health state. Moreover, the proposed model handles multiple alternative (imperfect and perfect) maintenance actions and associated spare parts orders and facilitates proactive decision making in the context of Condition-Based Maintenance (CBM). The proposed proactive decision model was validated in real industrial environment and was further evaluated with a comparative and a sensitivity analysis.

Suggested Citation

  • Alexandros Bousdekis & Gregoris Mentzas, 2019. "A Proactive Model for Joint Maintenance and Logistics Optimization in the Frame of Industrial Internet of Things," Springer Proceedings in Business and Economics, in: Angelo Sifaleras & Konstantinos Petridis (ed.), Operational Research in the Digital Era – ICT Challenges, pages 23-45, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-95666-4_3
    DOI: 10.1007/978-3-319-95666-4_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yan, Tao & Lei, Yaguo & Wang, Biao & Han, Tianyu & Si, Xiaosheng & Li, Naipeng, 2020. "Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    2. Zheng, Meimei & Ye, Hongqing & Wang, Dong & Pan, Ershun, 2021. "Joint Optimization of Condition-Based Maintenance and Spare Parts Orders for Multi-Unit Systems with Dual Sourcing," Reliability Engineering and System Safety, Elsevier, vol. 210(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:prbchp:978-3-319-95666-4_3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.