Synthesis of a Complex of Mathematical Models of Excavator Use Processes over Time

Article Preview

Abstract:

Comparison of experimental and calculated data of the excavator utilization factor in time (Ku) according to the current methods showed the absence of even a correlation between them r = 0.17, which indicates the inexpediency of using the basic models that are the basis of these methods. The reason for the low correspondence is that the excavation processes are complex random dynamic non-stationary processes, and the models that are the basis of almost all current methods are simple deterministic static models that cannot successfully operate at the level required for such processes. In the work with the application of the theory of mass service systems, a set of probabilistic dynamic non-stationary models in the form of Markov-Kolmogorov equations was developed to describe the probability of states, both for each of the selected subsystems of downtime of excavation works, and for the “excavator face” system as a whole. Comparison of the actual values of the coefficient (Ku) obtained as a result of the experiment allows us to recommend the developed set of models as the basis of the methodology for calculating Ku (r = 0.70).

You might also be interested in these eBooks

Info:

Periodical:

Pages:

248-256

Citation:

Online since:

January 2026

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2026 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Gavrish, P., Yusifov, V. Increasing the productivity of the CAT 349D2 excavator. (2023). Technical Sciences and Technologies, 3 (33), (2023) 103–110

DOI: 10.25140/2411-5363-2023-3(33)-103-110

Google Scholar

[2] Andrii Cherep, Determination of rational technological schemes for the completion of open-pits taking into account land reclamation IOP Conference Series Earth and Environmental Science 1319(1) (2024) 012013

DOI: 10.1088/1755-1315/1319/1/012013

Google Scholar

[3] Ng, F. Improving hydraulic excavator performance through in line hydraulic. F. Ng, J. A. Harding, J. Glass Mech. Syst. Signal Process (2016) 816-831

DOI: 10.1016/j.ymssp.2016.06.006

Google Scholar

[4] Prokopenko V., Pilov P., Cherep A. and Pilova D., Managing Mining Enterprise Productivity by Open Pit Reconstruction Eurasian mining 1 (2020) 42-46

DOI: 10.17580/em.2020.01.08

Google Scholar

[5] Sobko B., Lozhnikov O., Levytskyi V., Skyba G. Conceptual development of the transition from drill and blast excavation to non-blasting methods for the preparation of mined rock in surface mining. The Mining-Geology-Petroleum Engineering Bulletin. (2019) 21-28 https://

DOI: 10.17794/rgn.2019.3.3

Google Scholar

[6] Аnisimov О., Hrytsenko, L., Davydenko, N., Cherniaieva, O., & Sydorenko, I. Factors affecting the productivity of excavator and truck complexes. Technical Engineering, (2023) 262–270

DOI: 10.26642/ten-2023-1(91)-262-270

Google Scholar

[7] L. Ge, L. Quan, X. Zhang, Z. Dong, J. Yang Chin. J. Mech. Power Matching and Energy Efficiency Improvement of Hydraulic Excavator Driven with Speed and Displacement Variable Power Source Eng. 32:100(2023)9-12

DOI: 10.1186/s10033-019-0415-x

Google Scholar

[8] Azaryan V., Zhukov S. Development of the theory of quality management of ore flows of iron ore mining and processing plants. Scientific notes of the Vernadsky Tavrichesky National University: scientific journal. 29(68) 3 (2018) 89–94.

DOI: 10.31721/2306-5451-2018-1-46-159-164

Google Scholar

[9] Azaryan V.A. Algorithm of the technological and economic assessment of the application of the technology of controlling the quality of ore streams in quarries. Quality of mineral raw materials: Sat. science tr. – Kryvyi Rih: D.A. Chernyavskyi FLP, 2017. – P. 125–129.

Google Scholar

[10] F. Ng, J. A. Harding, J. Glass. Improving hydraulic excavator performance through in line hydraulic oil contamination monitoring Mech. Syst. Signal Process. (2016) 816-831

DOI: 10.1016/j.ymssp.2016.06.006

Google Scholar

[11] Аnisimov О., Hrytsenko, L., Davydenko, N., Cherniaieva, O., & Sydorenko, I. Factors affecting the productivity of excavator and truck complexes. Technical Engineering. (2023) 262–270

DOI: 10.26642/ten-2023-1(91)-262-270

Google Scholar

[12] Kryuchkov A., Besarabets Yu., Yevteeva L. Energy-saving operating modes of power excavators. // Current scientific research on resource-saving technologies for mining and processing of minerals. Collective monograph. – Sofia: Publishing House "St. Ivan Rylsky", 2020. - P. 353-368.

Google Scholar

[13] Kryuchkov, A., Evteeva, L System optimization of excavation works in a quarry using the criterion of minimum energy intensity. Bulletin of ZhDTU. Series "Technical Sciences", 1 (81) (2018) 257–260

DOI: 10.26642/tn-2018-1(81)-257-260

Google Scholar

[14] Kryuchkov, A. I., Evteeva L. I. Comparative analysis of local and system optimization of the operating mode of quarry excavators. Geoengineering: scientific and technical journal. (2020) 4 19–32 pp

Google Scholar

[15] Kryuchkov A.I., Yevteeva L.I. The influence of fluctuations and restrictions on the speed of digging and the coefficient of use of the excavator over time. Modern resource- and energy-saving technologies of mining production. Kremenchuk: KrNU named after of Ostrogradsky, (2016) 2(16). 74 - 83

Google Scholar

[16] O. M. Terentyev, A. I. Kryuchkov, A. Y. Kleshchov. Resonant energy-saving destruction of rocks: monograph. Volume 3. Plasma-mechanical destruction of faces. Monograph Kyiv: Igor Sikorsky Kyiv Polytechnic Institute. (2018) 147 p. – ISBN 978-617-7185-24-5

DOI: 10.30929/2074-1537.2018.1.55-65

Google Scholar

[17] Kryuchkov Anatoliy , Serhiienko Mykola The system of time characteristics and its influence on the excavation process in quarries. IOP Conference Series: Earth and Environmental Science, 1481(1) (2025) 012018. DOI 10.1088/1755-1315/1481/1/012018, https://iopscience.iop.org/article/10.1088/1755-1315/1481/1/012018, ISSN: 1755-1307, 1755-1315

DOI: 10.1088/1755-1315/1481/1/012018

Google Scholar

[18] Terentyev, O. M., Kleshchov, A. Y., Sergienko, M. I. Static-dynamic loosening of frozen rocks. Scientific and Technical Journal "GEOENGINEERING", Igor Sikorsky Kyiv Polytechnic Institute. (1), (2021) 28-39

DOI: 10.20535/2707-2096.1.2020.193971

Google Scholar

[19] Viktor Rozen, Pavlo Rozen, Anatolliy Kryuchkov, Mykola Sergienko. Formation of the Core Model of the Energy Consumption Management System of Production Systems. Studies in Systems, Decision and Control Modern Technologies in Energy and Transport II, (2025) pp.95-121 Publisher Springer Nature Switzerland

DOI: 10.1007/978-3-031-76650-3_7

Google Scholar

[20] Rozen V.,Rozen P. Determining the boundaries of the energy audit scope of work. Mathematical modelling. Vidnovluvana energetikaю 2 (2025) pp.67-74

DOI: 10.36296/1819-8058.2025.2(81)

Google Scholar

[21] Bakhtavar, E., & Mahmoudi, H. Development of a scenario-based robust model for the optimal truck-shovel allocation in open-pit mining. Computers & Operations Research, 115, (2020) 104539

DOI: 10.1016/j.cor.2018.08.003

Google Scholar