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DOI: 10.15507/2658-4123.031.202104.530-543

 

The Digital Twin for Agricultural Machinery Restoration Processes

 

Yuriy G. Sledkov
Director of Institute No. 3 “Control Systems, Informatics, and Electric Power Engineeringˮ, Moscow Aviation Institute (National Research University) (4 Volokolamskoe Shosse, Moscow 125993, Russian Federation), Cand.Sci. (Engr.), Professor, ORCID: https://orcid.org/0000-0001-6626-7283, This email address is being protected from spambots. You need JavaScript enabled to view it.

Leonid L. Khoroshko
Head of the Chair of System Modeling and Computer-Aided Design, Moscow Aviation Institute (National Research University) (4 Volokolamskoe Shosse, Moscow 125993, Russian Federation), Cand.Sci. (Engr.), Professor, ORCID: https://orcid.org/0000-0002-7487-8997, Researcher ID: P-2951-2014, This email address is being protected from spambots. You need JavaScript enabled to view it.

Pavel M. Kuznetsov
Professor of the Chair of System Modeling and Computer-Aided Design, Moscow Aviation Institute (National Research University) (4 Volokolamskoe Shosse, Moscow 125993, Russian Federation), Dr.Sci. (Engr.), ORCID: https://orcid.org/0000-0001-9237-3848, Researcher ID: K-8831-2018, This email address is being protected from spambots. You need JavaScript enabled to view it.

Anton O. Butko
Associate Professor of the Chair of System Modeling and Computer-Aided Design, Moscow Aviation Institute (National Research University) (4 Volokolamskoe Shosse, Moscow 125993, Russian Federation), Cand.Sci. (Engr.), ORCID: https://orcid.org/0000-0002-7933-3582, Researcher ID: J-8953-2018, This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract 
Introduction. Agricultural machinery provides the required level of mechanization. Sand abrasive, dirt, and open-air operations considerably accelerate the wear of mechanisms. An improper work plan and lack of complete information about the state of specific equipment units increase the time for repair and maintenance operations. The purpose of the study is to develop a digital twin model for the repair and restoration system of enterprises. The model will reduce material costs and allow for the best solutions to organize the work.
Materials and Methods. The model is developed on the basis of simulation modeling. The authors used the approach based on discrete-event modeling with the logical-mathematical apparatus for describing events occurring in a real object.
Results. Information support is formed taking into account the parameters of the production systems of repair enterprises and a mathematical model, which is a digital twin of the production system. This approach made it possible to automate the development of optimal plans for organizing repair work by repair enterprises, taking into account their interrelationships.
Discussion and Conclusion. The digital twin for the generalized production system of repair organizations allows developing options for the resource allocation and verifying them promptly to choose the best options through accumulating information about the most successful solutions. This will reduce the time for repair and restoration works, improve their quality and save labor.

Keywords: repair work, technological process, automation, mathematical model, database, software environment, productivity

The authors declare no conflict of interest.

For citation: Sledkov Yu.G., Khoroshko L.L., Kuznetsov P.M., Butko A.O. The Digital Twin for Agricultural Machinery Restoration Processes. Inzhenernyye tekhnologii i sistemy = Engineering Technologies and Systems. 2021; 31(4):530-543. doi: https://doi.org/10.15507/2658-4123.031.202104.530-543

Contribution of the authors:
Yu. G. Sledkov – academic advising.
L. L. Khoroshko – setting study problem, analyzing the literature data.
P. M. Kuznetsov – developing mathematical apparatus for a design model.
A. O. Butko – developing and describing program units and software.

All authors have read and approved the final manuscript.

Submitted 20.12.2020; approved after reviewing 10.02.2021;
accepted for publication 01.03.2021

 

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