Skip to main content

Digital Methods of Warehouse Logistics as a Tool to Accelerate Supply Chains

  • Conference paper
  • First Online:
XIV International Scientific Conference “INTERAGROMASH 2021"

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 246))

  • 1037 Accesses

Abstract

Accelerating supply chain links increasingly becomes a competitive advantage in satisfying demanding customers. A quick response to a customer's request increases the chances of success. This article discusses digital methods of warehouse logistics (including robotization of warehouses) as a tool to accelerate the link of warehouse logistics in the supply chain. The most successful cases of robotization of warehouses are considered. Based on the results of the considered cases, the barriers to the robotization of warehouses are identified. Indicators affecting the acceleration of the supply chain, as well as changes due to the introduction of digital technologies in warehouses, are determined. Conclusions are made about the existing waves of robotization, reference models of these waves are built, and conclusions are drawn about the advantages of modernizing warehouse logistics. The main indicators are considered due to which the effect of accelerating the supply chain is achieved. Possible directions for future research are considered.

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 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
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. Fedotov, A. A., Sergeev, S. M., Provotorova, E. N., Prozhogina, T. V., The digital twin of a warehouse robot for Industry 4.0. IOP Conference Series Materials Science and Engineering 862, 032061 (2020)

    Google Scholar 

  2. Robots replaced Amazon with 20,000 workers. HABR, https://habr.com/ru/company/pochtoy/blog/429622/, last accessed 2020/09/21

  3. Amazon gave up and raised employee salaries. HABR, https://habr.com/ru/company/pochtoy/blog/425849/, last accessed 2020/09/19

  4. Full robotization of Amazon warehouses postponed for 10 years. Infostart, https://infostart.ru/journal/news/tekhnologii/polnaya-robotizatsiya-skladov-amazon-otkladyvaetsya-na-10-let_1057778/, last accessed 2020/10/01

  5. Grzejszczak, T., Krzyzanowski, W., Galuszka, A.: Warehouse model for interaction planning of mobile robots. Conference: ESM®'2020 (The 34th annual European Simulation and Modelling Conference) At: LAAS Toulouse, France (2020)

    Google Scholar 

  6. Pinkam, N., Bonnet, F., Chong, N. Y.: Robot collaboration in warehouse. Conference: 2016 16th International Conference on Control, Automation and Systems (ICCAS) (2016)

    Google Scholar 

  7. Maydanova, S., Ilin, I.: Strategic approach to global company digital transformation. In: Proceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019: Education Excellence and Innovation Management through Vision 2020. pp. 8818–8833 (2019)

    Google Scholar 

  8. Iliinsky, A., Afanasiev, M., Metkin, D.: Digital technologies of investment analysis of projects for the development of oil fields of unallocated subsoil reserve fund. IOP Conf. Ser.: Mater. Sci. Eng. 497, 012028 (2019). https://doi.org/10.1088/1757-899X/497/1/012028

  9. Afanasev, M., Filatov, V., Myshovskaya, L., Gusev, V.: Logistical organization of shipments in the context of interaction of various modes of transport. MATEC Web Conf. 239, 03001 (2018). https://doi.org/10.1051/matecconf/201823903001

    Article  Google Scholar 

  10. When artificial intelligence defeats the magnetic marking of logistics complexes. Mair.ru Cloud Solution, https://mcs.mail.ru/blog/kogda-iskusstvennyj-intellekt-pobedit-magnitnuyu-razmetku-logisticheskih-kompleksov, last accessed 2020/10/19

  11. O.Tsymbal, A. Bronnikov, P. Mercorelli. Decision-making models for Robotic Warehouse. Conference: 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), 2020

    Google Scholar 

  12. Ilyinsky, A., Afanasyev, M., Ilin, I., Ilchenko, M., Metkin, D.: An Economic Model of CO2 Geological Storage in Russian Energy Management System. In: Murgul, V., Pasetti, M. (eds.) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018, pp. 201–209. Springer International Publishing, Cham (2019)

    Chapter  Google Scholar 

  13. Ilin, I.V., Bolobonov, D.D., Frolov, A.K.: Innovative business model as a factor in the successful implementation of IIoT in logistics enterprises. In: Proceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019: Education Excellence and Innovation Management through Vision 2020. pp. 5092–5102 (2019)

    Google Scholar 

  14. Ilin, I., Voronova, O., Knykina, T.: Improvement of the business model of network retail in FMCG sector. In: Proceedings of the 33rd International Business Information Management Association Conference, IBIMA 2019: Education Excellence and Innovation Management through Vision 2020. pp. 5112–5121 (2019)

    Google Scholar 

  15. Levina, A.I., Dubgorn, A.S., Iliashenko, O.Y. Internet of things within the service architecture of intelligent transport systems (2018) Proceedings—2017 European Conference on Electrical Engineering and Computer Science, EECS 2017, pp. 351–355. https://doi.org/10.1109/EECS.2017.72

  16. Andiyappillai, N.: Digital Transformation in Warehouse Management Systems (WMS) Implementations. International Journal of Computer Applications 177(45), 34–37 (2020)

    Article  Google Scholar 

  17. Vamsi, A. M., Deepalakshmi, P.: Deep Learning-based mobile robot for warehouse keeping. International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Vol. 9 Issue-1S4, December (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Dmitry Egorov or Anton Shaban .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Egorov, D., Shaban, A., Levina, A., Schuur, P., Gerrits, B., Levin, I. (2022). Digital Methods of Warehouse Logistics as a Tool to Accelerate Supply Chains. In: Beskopylny, A., Shamtsyan, M. (eds) XIV International Scientific Conference “INTERAGROMASH 2021". Lecture Notes in Networks and Systems, vol 246. Springer, Cham. https://doi.org/10.1007/978-3-030-81619-3_68

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-81619-3_68

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-81618-6

  • Online ISBN: 978-3-030-81619-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics