PDF To download article.

UDK 631.171:004.9

DOI: 10.15507/2658-4123.030.202004.711-722

 

Digitalization of Agricultural Machinery Rehabilitation

 

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.Sc. (Engineering), Professor, Researcher ID: P-2951-2014, ORCID: https://orcid.org/0000-0002-7487-8997, Scopus ID: 14039206400, 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), D.Sc. (Engineering), Researcher ID: K-8831-2018, ORCID: https://orcid.org/0000-0001-9237-3848, This email address is being protected from spambots. You need JavaScript enabled to view it.

Introduction. The aim of the study is to develop the basic principles for digitalization of the processes of providing the diagnostics and repair of agricultural machinery.
Materials and Methods. The specifics of agricultural machinery functioning are work in worst-on-worst operating conditions, such as significant abrasive contamination (soil particles, dust and other substances), operation in the conditions of exposure to natural climatic conditions, intensive use during the work shift and other factors that result in a regular need for testing and repairing. These factors significantly extend the time of maintenance and repair works. The study of the information environment for planning the distribution of agricultural machinery by repair enterprises has showed that the methods of this activity are not sufficiently developed. The authors propose a solution to the problem of rational distribution of agricultural machinery for repair and rehabilitation.
Results. This article describes the main principles for developing structural relationships of databases used to find rational solutions for organizing repair and rehabilitation of agricultural machinery. Due to the fact that the solution of such a problem is time-consuming and is carried out under conditions that dynamically change over time, a mathematical model for the production environment of repair organizations is proposed, which is implemented by means of computer technology. The requirements for models describing the state of the production system of repair organizations are defined. A model of a generalized production system is proposed.
Discussion and Conclusion. The model developed by the authors allows increasing the automation level of processes of distributing agricultural machinery by repair enterprises. The implementation of a new approach to planning repair works and distributing repairable agricultural machinery by repair enterprises will increase the efficiency of repair works, improve their quality parameters, reduce time, and optimize the structure of technological equipment of repair enterprises.

Keywords: repair works, technological process, automation, mathematical model, database, labor input, productivity

For citation: Khoroshko L.L., Kuznetsov P.M. Digitalization of Agricultural Machinery Rehabilitation. Inzhenerernyye tekhnologii i sistemy = Engineering Technologies and Systems. 2020; 30(4):711-722. DOI: https://doi.org/10.15507/2658-4123.030.202004.711-722

Contribution of the authors: L. L. Khoroshko – scientific guidance, formulation of research task, literature data analysis; P. M. Kuznetsov – mathematical apparatus development of design models.

All authors have read and approved the final manuscript.

Received 02.07.2020; revised 16.09.2020; published online 30.12.2020

 

REFERENCES

1. Akashev Z.T. Methodology of Improvement and Selection of the Structure of Mining Enterprises Technological Processes. Tyazheloye mashinostroeniye = Heavy Engineering. 2005; (12):17-19. (In Russ.)

2. Yeleneva J.Y., Kharin A.A., Yelenev K.S., et al. Corporate Knowledge Management in Ramp-Up Conditions: the Stakeholder Interests Account, the Responsibility Centers Allocation. CIRP Journal of Manufacturing Science and Technology. 2018; 23:207-216. (In Eng.) DOI: https://doi.org/10.1016/j.cirpj.2017.12.002

3. Andreev V.N., Prosvirina M.Ye. Evaluation of Production Management Quality as a Tool for Management System Formation and Development of Competitive Machine-Building Enterprises. Glavnyy mekhanik = Chief Mechanical Engineer. 2010; (8):27-31. (In Russ.)

4. Yagopolskiy A.G., Domnyshev A.A., Vorontsov Ye.A. Problems of Innovative Development of Mechanical Engineering in Russia. Innovatsii i investitsii = Innovation and Investment. 2019; (2):7-9. Available at: https://cyberleninka.ru/article/n/problemy-innovatsionnogo-razvitiya-mashinostroeniya-rossii (accessed 18.11.2020). (In Russ.)

5. Martinov G.M., Kozak N.V. Numerical Control of Large Precision Machining Centers by the AxiOMA Contol System. Russian Engineering Research. 2015; 35(7):534-538. (In Eng.) DOI: https://doi.org/10.3103/S1068798X15070114

6. Kuznetsov P.M., Tsyrkov G.A. The Purposeful Environment of Project and Operational Management. Informatsionnye tekhnologii v proektirovanii i proizvodstve = Information Technologies of CAD/CAM/CAE. 2017; (4):10-14. (In Russ.)

7. Tsyrkov A.V., Kuznetsov P.M., Tsyrkov G.A., et al. Project and Operations Management of Machine-Building Production. Vestnik Mordovskogo universiteta = Mordovia University Bulletin. 2018; 28(4):511-522. (In Russ.) DOI: https://doi.org/10.15507/0236-2910.028.201804.511-522

8. Borzenkov V.V., Dyakonova N.P. [Automated Design of Technological Process of Parts Processing on the Basis of Their Macroelement Structure]. Vestnik kompyuternykh i informatsionnykh tekhnologiy = Bulletin of Computer and Information Technologies. 2005; (1):18-21. Available at: http://vkit.ru/index.php/archive-rus/102-01 (accessed 18.11.2020). (In Russ.)

9. Maksimovskii D.E. Automation of Process Design by Design-Technological Parameterization. Russian Engineering Research. 2011; 31(9):870-872. (In Eng.) DOI: https://doi.org/10.3103/S1068798X1109019X

10. Kalyakulin S.Yu., Kuzmin V.V., Mitin E.V., et al. Informational Relational Models for Calculating the Cutting Conditions in Automatic Control Systems. Russian Engineering Research. 2018; 38(12):1049-1052. (In Eng.) DOI: https://doi.org/10.3103/S1068798X18120250

11. Kalyakulin S.Yu., Kuzmin V.V., Mitin E.V., et al. Designing the Structure of Technological Processes Based on Synthesis. Vestnik Mordovskogo universiteta = Mordovia University Bulletin. 2018; 28(1):77-84. (In Russ.) DOI: https://doi.org/10.15507/0236-2910.028.201801.077-084

12. Astapov V.Yu., Khoroshko L.L., Afshari P., et al. [CAD at Modeling of Modes of Technological Processes of Manufacture of Elements of Aircraft Constructions]. Trudy MAI = Works of MAI. 2016; 87. 20 p. Available at: http://trudymai.ru/upload/iblock/207/astapov_khoroshko_afshari-payam_khoroshko_rus.pdf?lang=ru&issue=87 (accessed 18.11.2020). (In Russ.)

13. Stephenson D.A., Agapiou J.S. Metal Cutting Theory and Practice. 3rd ed. Boca Raton: CRC Press; 2016. 969 p. (In Eng.) DOI: https://doi.org/10.1201/9781315373119

14. Weis B.X. From Idea to Innovation. A Handbook for Inventors, Decision Makers and Organizations. Heidelberg: Springer-Verlag Berlin; 2015. 263 p. (In Eng.) DOI: https://doi.org/10.1007/978-3-642-54171-1

15. Kuznetsov P.M., Khoroshko L.L. Digitization of Crushing and Milling Equipment Reconditioning. Gornyy informatsionno-analiticheskiy byulleten = Mining Informational and Analytical Bulletin. 2019; (10):195-205. (In Russ.) DOI: https://doi.org/10.25018/0236-1493-2019-10-0-195-205

16. Butko A.O., Briukhovetskii A.P., Grigoriev D.E., et al. Algorithms, Mechanisms and Procedures for the Computer-Aided Project Generation System. International Journal of Applied Engineering Research. 2017; 12(24):14199-14207. Available at: https://www.researchgate.net/publication/329683563_Algorithms_mechanisms_and_procedures_for_the_computer-aided_project_generation_system (accessed 18.11.2020). (In Eng.)

17. Butko A.O., Kolesnikov D.A. [Algorithms of the Subsystem of Project Construction Automation as Part of the Complex Analysis of Organizational and Technical Solutions]. Informatsionnye tekhnologii v proektirovanii i proizvodstve = Information Technologies in Design and Manufacturing. 2018; (3):3-9. Available at: http://izdat.ntckompas.ru/editions/magazine_news/detail.php?ELEMENT_ID=23671&SECTION_ID=159&ID=174 (accessed 18.11.2020). (In Russ.)

18. Dmitriyev B.M. Diagnosis of Technical State of Flex Production System. Remont, Vosstanovlenie, Modernizatsiya = Repair, Reconditioning, Modernization. 2018; (1):10-14. Available at: http://www.nait.ru/journals/number.php?p_number_id=2724 (accessed 18.11.2020). (In Russ.)

19. Timiryazev V.A., Khostikoev M.Z., Konoplev V.N., et al. Self-Programming of the Tool Trajectory in CNC Lathes. Russian Engineering Research. 2019; 39:154-157. (In Eng.) DOI: https://doi.org/10.3103/S1068798X19020114

  

Лицензия Creative Commons
This work is licensed under a Creative Commons Attribution 4.0 License.

Joomla templates by a4joomla