Preview

Strategic decisions and risk management

Advanced search

THE USE OF DIGITAL TWINS TO IMPROVE THE OPERATIONAL EFFICIENCY IN THE EXTRACTIVE INDUSTRIES

https://doi.org/10.17747/2618-947X-2023-3-292-311

Abstract

The article examines the impact of Digital Twins on the business processes of mining companies. Mining companies can optimise their operations, from stripping and mining to enrichment and transportation. By modelling different scenarios, identifying bottlenecks and making informed decisions, companies can improve resource efficiency, reduce downtime and increase productivity, making a positive impact on their operational efficiency. Predictive maintenance strategies implemented with the help of Digital Twins help increase efficiency by minimising unexpected equipment failures and maximising uptime.

The main technological effects of the use of Digital Twins in the mining industry, which affect the operational efficiency of the company, are: (1) an increase in the volume of output of commercial products after coal enrichment; (2) an increase in the coefficient of output to the production line of mining equipment.

These effects lead to an improvement in the operating efficiency of the mining company, which increases indicators such as EBITDA and cash balance at the end of the period. This impact on operating efficiency is achieved by increasing the volume of commercial products, improving the efficiency of production processes, and by reducing the fixed and operating costs of the business.

In order to assess the impact of the use of Digital Twin technology on mining companies, a methodology has been developed to assess the impact of the use of Digital Twin technology on mining companies. According to the results of the survey, a number of key production processes have been identified where the introduction of a Digital Twin is expected to have an impact.

As a result of the empirical study, the expected increase in EBITDA from the implementation of the Digital Twin was 28%, the actual increase in EBITDA over the study period was 21%. The expected increase in free cash at the end of the period was + 593 million rubles (+130%), the actual increase in free cash for the period under study was 441 million rubles (+96%).

The introduction of Digital Twins in mining companies has shown great potential for improving operational efficiency and solving complex challenges facing the industry.

About the Author

V. A. Svadkovsky
‘HC Evolution’ JSC (Moscow, Russia)
Russian Federation

Senior investment analyst at ‘HC Evolution’ JSC (Moscow, Russia).

Research interests: digital technologies and the effects of their implementation, the activities of large industrial coal mining companies, operational efficiency.



References

1. Borovkov A.I., Ryabov Yu.A., Maruseva V.M. (2018). Smart Digital Twins are the basis of a new paradigm of digital design and modeling of globally competitive products of a new generation. Springboard to Success, 13: 26. (In Russ.)

2. Grieves M. (2002). Virtual reality and the transformation of product development. Assembly Automation, 22(4): 312-319. (In Russ.)

3. Isaev R.A. (2023). Management of the organization’s OT architecture: Design, analysis, optimization and transformation. Moscow, Infra-M. (In Russ.)

4. Samosudov M.V. (2018). The concept of a new generation program for automation of activities. In: Step into the future: Artificial intelligence and the digital economy. Revolution in management: A new digital economy or a new world of machines. Proceedings of the II International Scientific Forum, 5. Moscow, GUU Publishing House, 40-50. https://guu.ru/wp-content/uploads/forum_bl_v55.pdf. (In Russ.)

5. Alam K.M., Saddik A. (2017). El C2PS: A Digital Twin architecture reference model for the cloud-based cyberphysical systems. IEEE Access, 5: 2050.

6. Arenkov I., Tsenzharik M. (2019). Digital technologies in supply chain management. Atlantis Highlights in Computer Sciences, 1: 720-734.

7. Bao Q. (2020). Ontology-based modeling of part Digital Twin oriented to assembly. Journal of Engineering Manufacture, 13(4): 534-556.

8. Barricelli B.R., Casiraghi E., Fogli D. (2019). A Survey оn Digital Twin: Definitions, characteristics, applications, and design implications. IEEE Access, 7: 289-301.

9. Glaessgen E., Stargel D. (2012). The Digital Twin paradigm for future NASA and U.S. air force vehicles. 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. https:// doi.org/10.2514/6.2012–1818.

10. Grieves M., Vickers J. (2017). Digital Twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary Perspectives on Complex Systems: New Findings and Approaches, 16(4): 85-113.

11. Karapetyan D., Mitrovic Minic S., Malladi K.T., Punnen A.P. (2020). Satellite downlink scheduling problem: A case study. Omega, 27(2): 115-129.

12. Kritzinger W., Karner M., Traar G., Henjes J., Sihn W. (2018). Digital Twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine, 51: 334-346.

13. Merdan M., Moser T., Sunindyo W., Biffl S., Vrba P. (2022). Workflow scheduling using multi-agent systems in a dynamically changing environment. Journal of Simulation, 118-129.

14. Negri E., Fumagalli L., Macchi M. (2017). A review of the roles of Digital Twin in CPS-based production systems. Procedia Manufacturing, 11: 939-948.

15. Saddik A.E. (2018). A Digital Twin architecture reference model for the cloud-based cyber-physical systems. IEEE MultiMedia, 25(2): 87.

16. Stark R., Damerau T. (2019). Digital Twin, CIRP. In: Encyclopedia of Production Engineering. Berlin, Heidelberg, Springer, 66: 1.

17. Tao F., Qi Q., Liu A., Kusiak A., Zhou L. (2019). Digital Twins and cyber-physical systems. Toward smart manufacturing and Industry 4.0: Correlation and comparison. Engineering, 5(4), 653-661.

18. Trauer J., Schweigert-Recksiek S., Engel C., Spreitzer K., Zimmermann M. (2020). What is a Digital Twin? In: Design Conference, Proceedings of the Design Society, 1: 757. DOI:10.1017/dsd.

19. Zhuang Ñ., Liu J., Xiong H. (2018). Digital Twin - based smart production management and control framework for the complex product assembly shop-floor. International Journal of Advanced Manufacturing Technology, 96: 1149.


Review

For citations:


Svadkovsky V.A. THE USE OF DIGITAL TWINS TO IMPROVE THE OPERATIONAL EFFICIENCY IN THE EXTRACTIVE INDUSTRIES. Strategic decisions and risk management. 2023;14(3):292-311. https://doi.org/10.17747/2618-947X-2023-3-292-311

Views: 494


ISSN 2618-947X (Print)
ISSN 2618-9984 (Online)