| Issue |
SHS Web Conf.
Volume 93, 2021
3rd International Scientific Conference on New Industrialization and Digitalization (NID 2020)
|
|
|---|---|---|
| Article Number | 03005 | |
| Number of page(s) | 7 | |
| Section | Modern Management Technologies and the Development of Knowledge-Intensive Activities | |
| DOI | https://doi.org/10.1051/shsconf/20219303005 | |
| Published online | 12 January 2021 | |
Resilient Supply Chain Management Model
1 Russian University of Transport (MIIT), 127994 Moscow, Russia
2 Plekhanov Russian University of Economics, 117997 Moscow, Russia
3 Financial University under the Government of the Russian Federation, 125993 Moscow, Russia
4 Belarusian National Technical University, 220013 Minsk, Belarus
5 Moscow Automobile and Road Construction State Technical University (MADI), 125319, Moscow, Russia
* Corresponding author: larin_on@mail.ru
The strategy for the development of the supply chain should ensure a high level of fault tolerance of all links when exposed to adverse factors. The article analyzes the impact on the stability of the supply chain of two types of influences: failure and disruption. The low stability of the supply chain appears in the stoppage of work in case of any disruptions and failures. With moderate stability, disruptions do not give up a significant impact on the operation of the supply chain, and failures lead to an increase in operating costs to maintain the stability of work processes. With a high level of stability, failures can cause disruptions in the operations of individual links. In case of disruptions, response models are applied based on the control of process parameters, the subsequent analysis of the causes of disruptions and the development of measures to restore the normal operation of the links in the supply chain. Effective disruption response involves the use of proactive response models. For this, it is necessary to ensure flexibility and transparency of processes in all links of the supply chain based on digital services for material flow control and mining of big data.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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