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Breaking through the bottlenecks using artificial intelligence

In: Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 27

Author

Listed:
  • Feldt, Julia
  • Kontny, Henning
  • Wagenitz, Axel

Abstract

Purpose: Performance of Supply Chain is highly dependent on weak spots, so-called bottlenecks. This research paper presents the findings from the analysis of operation processes of a mid-sized producing company and the digital solution for opening up the bottlenecks in order to achieve effectiveness by cutting down the order lead time. Methodology: The study is employing several rounds of simulation based on processes and data from a manufacturing company. Findings: Simulation results demonstrate that by allowing a system to take autonomous decisions for production planning based on current changes in environment such as new customer order or available capacity, the order lead time can be shortened significantly, while granting additional flexibility and robustness to the whole supply chain. Originality: The findings of this research reveal new insights on potentials of artificial intelligence in solving of existing issues within supply chain IT systems.

Suggested Citation

  • Feldt, Julia & Kontny, Henning & Wagenitz, Axel, 2019. "Breaking through the bottlenecks using artificial intelligence," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg Int, volume 27, pages 30-56, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
  • Handle: RePEc:zbw:hiclch:209368
    DOI: 10.15480/882.2463
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    References listed on IDEAS

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    1. Wagner, Julia & Kontny, Henning, 2017. "Use case of self-organizing adaptive supply chain," 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 255-273, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Mihalis Giannakis & Michalis Louis, 2016. "A Multi-Agent Based System with Big Data Processing for Enhanced Supply Chain Agility," Post-Print hal-01353916, HAL.
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    Cited by:

    1. Feldt, Julia & Kontny, Henning & Niemietz, Frank, 2020. "How disruptive start-ups change the world of warehouse logistics," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 3-24, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

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