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Methodology for a dump design optimization in large-scale open pit mines

Modern large-scale open pit mines move hundreds of thousands of tonnes of material daily, from the loading sources to the destination zones, whether these are massive mine dumps or, to a lesser extent, to the grinding mills. Mine dumps can be classified as leach or waste dumps, depending upon their economic viability to be processed in-place, a condition that has experienced great progress in the last decades and has reconfigured the open pit haulage network with an increase in the number of dumps. Therefore, new methods for dump design optimization are of the highest priority in mine planning management. This paper presents a methodology to model and optimize the design of a dump by minimizing the total haulage costs. The location and design of these dumps will be given mainly by the geological characteristics of the mineral, tonnage delivered, topographical conditions, infrastructure capital and transportation costs. Spatial and physical design possibilities, in addition, provide a set of parameters of mathematical and economic relationship that creates opportunities for modelling and thus facilitates the measurement and optimization of ultimate dump designs. The proposed methodology consists of: (1) Formulation of a dump model based on a system of equations relying on multiple relevant parameters; (2) Solves by minimizing the total cost using linear programming and determines a "preliminary" dump design; (3) Through a series of iterations, changes the "preliminary" footprint by projecting it to the topography and creates the ultimate dump design. Finally, an application for a waste rock dump illustrates this methodology.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/626612
Date05 October 2017
CreatorsPuell Ortiz, Jorge
ContributorsUniv Arizona, Dept Min & Geol Engn, Department of Mining and Geological Engineering, University of Arizona Tucson USA
PublisherTAYLOR & FRANCIS AS
Source SetsUniversity of Arizona
LanguageEnglish
Detected LanguageEnglish
TypeArticle
Rights© 2017 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
Relationhttps://www.cogentoa.com/article/10.1080/23311916.2017.1387955

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