Selection of parameters
for the development of mineral deposits
A.O. Khorolskyi*, V.G. Hrinov1
1Institute for
Physics of Mining Processes the National Academy Sciences of Ukraine,
Dnipro, Ukraine
1* Corresponding
author: e-mail: khorolskiyaa@ukr.net
Physical and
technical problems of mining production, 2020, (22), 118-140.
https://doi.org/10.37101/ftpgp22.01.009
full
text (pdf)
ABSTRACT
Purpose. To develop a new
approach to the effective development of mineral deposits by creating
optimal design technology.
Methodology. To model the
process of developing mineral deposits, a dynamic programming model is proposed that allows you to develop strategies for
the optimal process of designing, developing, operating. To make decisions
at the stage of parameter estimation, a decomposition approach is applied.
For decision making, algorithms and methods of
dynamic programming are proposed.
Findings. A new approach to
the estimation and selection of parameters is presented, a characteristic
feature of which is that the mineral itself is not considered “as a final
product” that should be extracted, but only as an intermediate link in the
structure of energy generation, metal smelting, etc. This allows us to
consider operation process due to changes in stock status, which in turn
forms a development strategy. The development strategy provides for the
construction of scenarios (economic, environmental) within the framework of
which a "narrow" task is solved related
to the organization of work, cost optimization, etc.
Originality. For the first
time, a mechanism is described for shaping the
efficiency of field development, which provides for a hierarchical
structure based on the category of “quality”, which in turn forms
strategies; strategies form scenarios, and scenarios contain parameters;
optimization of each parameter involves the assessment of priority control
factors. For the first time, an algorithm has been
proposed for the optimal design of development of a mineral deposit,
which involves determining the volume of production, minimizing risks,
determining parameters that meet the optimality criterion and their further
optimization.
Practical
implications. For the first time, methods and results of studies on the optimal
design of the exploitation parameters of deposits of valuable minerals of
Ukraine are proposed, which are the basis of the
methodology for solving complex problems of optimizing the parameters of a
mining and processing enterprise and correspond to the modern level of
information technology.
Keywords:: rare
and precious metals, opening of a deposit, dynamic programming, inventory
status, algorithm, software, optimization, effective operation, anchored
project, investment attractiveness
REFERENCES
1.
Grinev, V.G. (2008).
Otsenka perspektiv povyisheniya effektivnosti polucheniya konechnoy produktsii iz uglya.
Fiziko-tehnicheskie problemyi gornogo proizvodstva, (11), 126-135.
2.
Grinov, V.G., & Horolskiy, A.O. (2018). MozhlivostI
efektivnogo osvoennya rudnih rodovisch iz zapasami ridkisnih i blagorodnih metaliv. Fiziko-tehnicheskie problemyi gornogo proizvodstva, (20), 113-122.
3.
Grin'ov, V.G., Horol's'kyj,
A.O., & Kaliushhenko, O.P. (2019). Rozroblennja ekologichnyh scenarii'v efektyvnogo osvojennja cinnyh rodovyshh korysnyh kopalyn. Mineral'ni resursy Ukrai'ny,
(2), 46-50.
4.
Kursunoglu, N., & Onder, M. (2015). Selection of an appropriate fan for
an underground coal mine using the Analytic Hierarchy
Process. Tunnelling and Underground
Space Technology, (48), 101-109.
5.
Bogdanovic, D., Nikolic, D.,
& Ilic, I. (2012). Mining method selection by
integrated AHP and PROMETHEE method. Anais
da Academia Brasileira de Ciências,
84(1), 219-233.
6.
Iphar, M., & Alpay, S. (2019). A mobile application based on
multi-criteria decision-making methods for underground mining method
selection. International Journal of Mining, Reclamation and Environment.
33(7), 480-504.
7.
Hayati, M., Rajabzadeh, R., & Darabi,
M. (2015). Determination of Optimal Block Size in Angouran
Mine Using VIKOR Method. J. Mater. Environ. Sci. 6(11),
3236-3244.
8.
Huang, W. et al. (2015). Stability assessment of
underground mined-out areas in a gold mine based on complex system theory. Geotechnical and Geological
Engineering.
33(5), 1295-1305.
9.
Naghadehi, M.Z., Mikaeil, R., & Ataei, M.
(2009). The application of fuzzy analytic hierarchy process (FAHP) approach
to selection of optimum underground mining method for Jajarm
Bauxite Mine, Iran. Expert
Systems with Applications, 36(4),
8218-8226.
10.
Balusa, B.C., & Singam, J. (2018). Underground mining method selection
using WPM and PROMETHEE. Journal
of the Institution of Engineers (India): Series D. 99(1),
165-171.
11.
Krzak, M. (2013). The
Evaluation Of An Ore Deposit Development Prospect
Through Application Of The" Games Against Nature" Approach. Asia-Pacific Journal of Operational Research. 30(6),
1350029.
12.
Khorolskyi, A.O., & Hrinov, V.H., (2018). Proektuvannia
tekhnolohichnykh skhem hirnychoho vyrobnytstva v umovakh nevyznachenosti. Fyzyko-tekhnycheskye problemy hornoho proyzvodstva, (20),
132-146.
13.
Lee, S., & Park, I. (2013). Application of
decision tree model for the ground subsidence hazard mapping near abandoned
underground coal mines. Journal
of environmental management.
(127), 166-176.
14.
Hrinov, V. & Khorolskyi, A. (2018). Improving the Process of Coal
Extraction Based on the Parameter Optimization of Mining Equipment. In E3S
Web of Conferences, Ukrainian School of Mining Engineering. (Vol. 60. p. 00017). EDP Sciences. doi.org/10.1051/e3sconf/20186000017
15.
Kulshreshtha, M., & Parikh
J.K. (2002). Study of efficiency and productivity growth in opencast and
underground coal mining in India: a DEA analysis. Energy Economics. 24(5), 439-453.
16.
Li, P. et al. (2011). Time series prediction of
mining subsidence based on a SVM. Mining
Science and Technology (China). 21(4), 557-562.
17.
Bakhtavar, E., Shahriar, K., & Mirhassani,
A. (2012). Optimization of the transition from open-pit to underground
operation in combined mining using (0-1) integer programming. Journal of
the Southern African Institute of Mining and Metallurgy. 112(12), 1059-1064.
18.
Erdogan, G. et al. (2017). Implementation and
comparison of four stope boundary optimization algorithms
in an existing underground mine. International Journal of Mining, Reclamation and Environment.
31(6), 389-403.
19.
Dimitrakopoulos, R., & Ramazan, S. (2008). Stochastic integer programming for
optimising long term production schedules of open
pit mines: methods, application and value of stochastic solutions. Mining Technology. 117(4), 155-160.
20.
Nazimko, V., Illiashov, M., & Youshkov,
E. (2014). Соmputer-aided multy-object distributtion
system for prompt project management. Progressive Technologies of Coal, Coalbed
Methane, and Ores Mining, 53.
21.
Beaulieu, M., & Gamache,
M. (2006). An enumeration algorithm for solving the fleet management
problem in underground mines. Computers & operations research. 33(6),1606-1624.
22.
Grynev, V.G., Yzakson, V.Ju.,
& Zubkov, V.P. (1999). Reshenye gornikh zadach na
EVM pry osvoenyy rudnuh
mestorozhdenyj. Novosybyrsk:
Nauka, Sybyrskaja yzdatel'skaja fyrma RAN, 215 p.
23.
Mamaikin, O., Sotskov, V., Demchenko, Y.,
& Prykhorchuk, O. (2018). Productive flows
control in coal mines under the condition of
diversification of production. In E3S Web of Conferences (Vol. 60,
p. 00008). EDP Sciences. doi.org/10.1051/e3sconf/20186000008
24.
Fomychov, V., Mamaikin, O., Demchenko, Y., Prykhorchuk, O., & Jarosz,
J. (2018). Analysis of the efficiency of geomechanical
model of mine working based on computational and field studies. Mining of Mineral
Deposits,
12(4), 46–55. https://doi.org/10.15407/mining12.04.046
25.
Petlovanyi, M., Kuzmenko, O., Lozynskyi, V., Popovych, V., Sai, K., & Saik,
P. (2019). Review of man-made mineral formations
accumulation and prospects of their developing in mining industrial
regions in Ukraine. Mining of Mineral Deposits, 13(1),
24-38. https://doi:10.33271/mining13.01.024
26.
Khomenko, O., Kononenko,
M., & Myronova, I. (2013). Blasting works
technology to decrease an emission of harmful matters into the mine
atmosphere. Mining Of Mineral
Deposits,
231-235. http://dx.doi.org/10.1201/b16354-43
27.
Khomenko, O., Kononenko,
M., & Myronova, I. (2017).
Ecologic-and-technical aspects of iron-ore underground mining. Mining of mineral
deposits, 11(2),
59-67 https://doi.org/10.15407/mining11.02.059
28.
Hrynev V.H., & Khorolskyi A.A.
(2017). Obosnovanye parametrov
vybora komplektatsii ochysnoho oborudovanyia s uchetom oblasty ratsyonalnoi ekspluatatsyy. Vesty Donetskoho hornoho instytuta, 1(40), 139–144.
doi.org/10.31474/1999-981x-2017-1-139-144.
29.
Brazil, M. et al. (2005). Cost optimisation for
underground mining networks. Optimization and engineering. 6(2), 241-256.
30.
Liu, Q., Li, X., & Meng,
X. (2019). Effectiveness research on the multi-player evolutionary game of coal-mine safety regulation in China based on system
dynamics. Safety science. (111), 224-233.
31.
Musingwini, C., Minnitt, R.C.A., & Woodhall,
M. (2007). Technical operating flexibility in the analysis of mine layouts
and schedules. Journal of the Southern African Institute of Mining and
Metallurgy. 107(2), 129-136.
32.
Khorolskyi A.O., & Hrinov V.H.
(2017). Systemni pryntsypy
ta otsinochnyi kryterii
nadiinosti pry optymizatsii
tekhnolohichnykh skhem vuhilnykh rodovyshch. Visnyk Zhytomyrskoho
derzhavnoho tekhnolohichnoho
universytetu. Seriia: Tekhnichni nauky, 80(2),
199–207. https://doi.org/10.26642/tn-2017-2(80)-225-233.
33.
Salli, S., Pochepov, V., & Mamaykin,
O. (2014). Theoretical aspects of the potential technological schemes
evaluation and their susceptibility to innovations. In Progressive
Technologies of Coal, Coalbed Methane, and Ores Mining (pp. 491-496).
34.
Vladyko, O., Kononenko, M., & Khomenko, O. (2012). Imitating modeling stability of mine workings. Geomechanical processes during underground mining, 147-150.
35.
Grynev, V.G., Petrov, A.N., &
Zubkov, V.P. (1994). Opredelenye oblasty proektyrovanyja effektyvnoj razrabotky rudnuh mestorozhdenyj Jakutyy.
Gornoe delo v
Arktyke, S.-Peterburg.
36.
Horolskiy, A.A., & Grinev, V.G. (2018). Proektirovanie
tehnologicheskih shem ochistnogo oborudovaniya s ispolzovaniem
setevyih modeley: opyit i perspektivyi.
Gornaya mehanika i mashinostroenie,
(4), 12-21.
37.
Hrinov, V.H., Khorolskyi, A.O., & Mamaikin,
O.R. (2019). Dekompozytsiinyi pidkhid
pry pobudovi system heneratsii
enerhii u vuhlepromyslovykh
rehionakh. Visti
Donetskoho hirnychoho instytutu, (44),
116-126. doi.org/10.31474/1999-981x-2019-1-116-126
38.
Hrinov, V.H., Khorolskyi, A.O., & Mamaikin,
O.R. (2019). Otsinka stanu
ta optymizatsiia parametriv
tekhnolohichnykh skhem vuhilnykh shakht. Visnyk Kryvorizkoho natsionalnoho universytetu, (48), 31-37. doi:
10.31721/2306-5451-2019-1-48-31-37
39.
Khorolskyi, A.O., Hrinov, V.H., Mamaikin, O.R.
(2019). Optymizatsiia stiikosti
funktsionuvannia pidsystem
ochysnoho vyboiu. Suchasni resursoenerhozberihaiuchi tekhnolohii hirnychoho vyrobnytstva,
(23), 85-103. doi:
10.30929/2074-1537.2019.1.85-103
40.
Khorolskyi A.O., & Hrinov V.H.
(2017). Systemni pryntsypy
ta otsinochnyi kryterii
nadiinosti pry optymizatsii
tekhnolohichnykh skhem vuhilnykh rodovyshch. Visnyk Zhytomyrskoho
derzhavnoho tekhnolohichnoho
universytetu. Seriia: Tekhnichni nauky, 80(2),
199–207. https://doi.org/10.26642/tn-2017-2(80)-225-233.
41.
Bellman, R., & Drejfus,
S. (1965). Prykladnie zadachy dynamycheskogo programmyro-vanyja. M.:
Nauka.
42.
Cargile, J. (1995). qualities.
in Honderich, T. (Ed.)
(2005). The Oxford Companion to Philosophy (2nd ed.). Oxford
43.
Mironova, I., & Pavlichenko, A. (2013). Analysis of air pollution
levels during underground ore mining. Mining
of Mineral Deposits, 7(3),
261-266. http://dx.doi.org/10.15407/mining07.03.261
44.
Mironova, I., & Borysovs’ka, O. (2014). Defining the parameters of the
atmospheric air for iron ore mines. Progressive Technologies of Coal,
Coalbed Methane, and Ores Mining, 333-339. http://dx.doi.org/10.1201/b17547-57.
45.
Gorova, A., Kolesnyk, V., & Myronova,
I. (2014). Increasing of environmental safety level during underground
mining of iron ores. Mining of Mineral
Deposits,
8(4), 473-479. http://dx.doi.org/10.15407/mining08.04.473
46.
Khomenko, O., Kononenko,
M., Myronova, I., & Sudakov,
A. (2018). Increasing ecological safety during underground mining of
iron-ore deposits. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu,
(2), 29-38. http://dx.doi.org/10.29202/nvngu/2018-2/3
47.
Khomenko, O., Kononenko,
M., & Savchenko, M. (2018). Technology of
underground mining of ore deposits. https://doi.org/10.33271/dut.001
48.
Hrinov, V.H., & Khorolskyi, A.O. (2019). Optymalne
proektuvannia parametriv
hirnychozbahachuvalnykh pidpryiemstv
dlia ratsionalnoho osvoiennia tsinnykh rodovyshch Ukrainy. Fyzyko-tekhnycheskye problemy hornoho proyzvodstva, (21), 128-145.
https://doi.org/10.37101/ftpgp21.01.008.
49.
Bellman, R. (1957). Dynamic Programming. Princeton University Press.
50.
Sckwarts, W. (1968). Dunamishes programmleriew erlautert am Belsplet der Optimierung Von Kupfergewinnungsverfahren.
Erzmetall, (10), 455-460.
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