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Data mining and fault tolerance in warehousing

In: Digitalization in Supply Chain Management and Logistics: Smart and Digital Solutions for an Industry 4.0 Environment. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 23

Author

Listed:
  • Reining, Christopher
  • Bousbiba, Omar
  • Jungen, Svenja
  • Ten Hompel, Michael

Abstract

This paper surveys the significance of data mining techniques and fault tolerance in future materials flow systems with a focus on planning and decision-making. The fundamental connection between data mining, fault tolerance, and materials flow is illustrated. Contemporary developments in warehousing are assessed to formulate upcoming challenges. In particular, the transition towards distributed systems and the increasing data volume is examined. The significance of taking fault tolerance into account is emphasized. Ultimately, research issues are derived by conflating the previous findings. They comprise a holistic approach towards the integration of data science and fault tolerance techniques into future materials flow systems. Tackling these research issues will help to proactively harmonize the data representation to specific data mining techniques and increase the reliability of such systems.

Suggested Citation

  • Reining, Christopher & Bousbiba, Omar & Jungen, Svenja & Ten Hompel, Michael, 2017. "Data mining and fault tolerance in warehousing," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Digitalization in Supply Chain Management and Logistics: Smart and Digital Solutions for an Industry 4.0 Environment. Proceedings of the Hamburg Inter, volume 23, pages 215-232, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:209310
    DOI: 10.15480/882.1464
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