Application of survival theory in Mining industry

Enkhbat Rentsen; N. Tungalag; J. Enkhbayar; O. Battogtokh; L. Enkhtuvshin

doi:10.3934/naco.2020036

Article Contents

2021, Volume 11, Issue 3: 443-448. Doi: 10.3934/naco.2020036

This issue Previous Article Properties of higher order preinvex functions Next Article The proximal methods for solving absolute value equation

Application of survival theory in Mining industry

1.
Institute of Mathematics and Digital Technology, Mongolian Academy of Sciences, National University of Mongolia
2.
National University of Mongolia
3.
Erdenet Mining Corporation, Erdenet, Mongolia

^*Corresponding author: Enkhbat Rentsen
^*Corresponding author: Enkhbat Rentsen

Received: April 2020

Revised: June 2020

Early access: August 2020

Published: September 2021

This work was supported by the project of Business School of National University of Mongolia

Abstract / Introduction Full Text(HTML) Related Papers Cited by

Abstract

The paper deals with an application of survival theory in mineral processing industry. We consider the problem of maximizing copper recovery and determine the best operating conditions based on survival theory. The survival of the system reduces to a problem of maximizing a radius of a sphere inscribed into a polyhedral set defined by the linear regression equations for a flotation process. To demonstrate the effectiveness of the proposed approach, we present a case study for the rougher flotation process of copper-molybdenum ores performed at the Erdenet Mining Corporation(Mongolia).

Keywords:

Mathematics Subject Classification: Primary: 90C05, 90C25; Secondary: 90C99.

Citation:

FullText(HTML)

Related Papers

Cited by

References

[1]	L. T. Ashepkov and U. Badam, Models and Methods of Survival Theory for Controlled System, Vladivostok: DalNauka, 2006.
[2]	U. Badam, A simple model of improving survival in economical systems, Optimization of Control (Eds. P. M. Pardalos, I. Tseveendorj and R. Enkhbat), World Scientific, (2003), 287–295.
[3]	U. Badam, Optimality conditions for problems of survival theory, Izvestiya Vuzov, 2 (2002), 18-22.
[4]	U. Badam, Models and problems of survival theory for linear discrete system, Intellect and Control, (2002), 35–50.
[5]	U. Badam, R. Enkhbat and Ts. Batchimeg, Application of survival theory in taxation, Journal of Indusdrial and Management Optimization, accepted and to appear in 2021.
[6]	D. Carl Freeman, Lionel G. Klikoff and He nry Eyringt, Applications of the survival theory to ecology, Proc. Nat. Acad. Sci. USA, 11 (1974), 4332-4335.
[7]	S. S. Cham. Rath, H. Sahoo and B. Das, Optimization of flotation variables for the recovery of hematite particles from BHQ Ore, Int. J. Miner. Metall. Mater., 20 (2013), 605-611.
[8]	R. Enkhbat, Global optimization approach to Malfatti's problem, Journal of Global Optimization, 65 (2016), 3-39. doi: 10.1007/s10898-015-0372-6.
[9]	R. Enkhbat, Convex maximization formulation of general sphere packing problem, Izv. Irkutsk. Gos. Univ. Ser. Mat., 31 (2020), 142-149.
[10]	R. Enkhbat, T. V. Gruzdeva and M. V. Barkova, D. C. programming approach for solving an applied ore-processing problem, Journal of Indusdrial and Management Optimization, 14 (2018), 613-623. doi: 10.3934/jimo.2017063.
[11]	Thomas R. Fleming and David P. Harrington, Counting Processes and Survival Analysis, Wiley, 1991.
[12]	T. V. Gruzdeva, A. V. Ushakov and R. Enkhbat, A bioobjective d.c programming approach to optimization of rougher flotation process, Computers and Chemical Engineering, 108 (2018), 349-359.
[13]	C. Huber, N. Limnios, M. Meshbah and M. Nikulin, Mathematical Methods in Survival Analysis, Reliability and Quality of Life, Wiley, 2008. doi: 10.1002/9780470610985.
[14]	X. Liu, Survival Analysis(Models and Applications), Wiley, 2012.
[15]	M. Maldonado, D. Sbarbaro and E. Lizama, Optimal control of a rougher flotation process based on dynamic programming, Miner. Eng., 20 (2007), 221-232.
[16]	D. A. Mendez, E. D. Gálvez and L. A. Cisternas, State of the art in the conceptual design of flotation circuits, Int. J. Miner. Process., 90 (2009), 1-15.
[17]	D. Pirouzan, M. Yahyaei and S. Banisi, Pareto based optimization of flotation cells configuration using an oriented genetic algorithm, Int. J. Miner. Process., 126 (2014), 107-116.
[18]	B. J. Shean and J. J. Cilliers, A review of froth flotation control, Int. J. Miner. Process., 100 (2011), 57-71.
[19]	A. S. Strekalovsky, Global optimality conditions and exact penalization, Optimization Letters, 13 (2019), 597-615. doi: 10.1007/s11590-017-1214-x.
[20]	G. Zimmermann, From Basic Survival Analytic Theory to a Non-Standard Application, Springer, 2017.