Sergey Yevgenievich Barykin
Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251, St. Petersburg, Russian Federation.

Andrey Aleksandrovich Bochkarev
St. Petersburg School of Economics and Management, Department of Logistics and Supply Chain Management, National Research University, Higher School of Economics, Saint-Petersburg branch, Str. Kantemirovskaya, 3A, 194100, St. Petersburg, Russian Federation.

Olga Vladimirovna Kalinina
Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251, St. Petersburg, Russian Federation.

Vladimir Konstantinovich Yadykin
Competence Center of the National Technological Initiative, Direction of New Production Technologies, Institute of Advanced Production Technologies, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251, St. Petersburg, Russian Federation.

DOI https://doi.org/10.33889/IJMEMS.2020.5.6.111

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Abstract

There is currently a discussion going on in the scientific community about using digital twins and modeling to manage risks in the supply chains. This need for constructing digital twins is caused by the low reliability and stability of supply chains due to the faults in their operation. These faults are a result of risks in the supply chains which can be consolidated into two types. The first type is operational risks. These are the current risks of the supply chain itself caused by an uncer-tainty of supply and demand as well as by an obstructed flow of information along the supply chain. The second type is critical risks caused by force majeure. These risks disrupt the normal operation of the supply chain and critically reduce the most important performance indicators of the company such as annual income and profits. Risks happen due to natural or man-made causes such as fires and floods in the distribution centers or at production facilities, legal disputes with sup-pliers, strikes, terrorist attacks on logistics facilities and others. Dynamic simulation and analytical optimization are two dominant technologies for managing risks of the supply chains, which helps to increase their reliability and stability if failures occur. Through optimizing and simulating of the supply chains, companies can generate new information about the impact of failure and influence the supply chain and its performance by looking at various scenarios that simulate the locations of failures, the duration and recovery policies. An analysis of the literary sources shows that there is no single approach to build the concept for a supply chain digital twin. This article gives an overview of the literature according to this problem and offers the author's point of view on the concept for a supply chain digital twin.

Keywords- Supply chains, Optimization, Simulation, Digital twin.

Citation

Barykin, S. Y., Bochkarev, A. A., Kalinina, O. V., & Yadykin, V. K. (2020). Concept for a Supply Chain Digital Twin. International Journal of Mathematical, Engineering and Management Sciences, 5(6), 1498-1515. https://doi.org/10.33889/IJMEMS.2020.5.6.111.