Cost analysis of material handling systems in open pit mining: Case study on an iron ore prefeasibility study

Marco de Werk, Burak Ozdemir, Bellal Ragoub, Tyrrell Dunbrack and Mustafa Kumral

The Engineering Economist, 2017, vol. 62, issue 4, 369-386

Abstract: Selection of the optimal material handling system is one of the most significant decisions to be made in mineral industries. Rapid economic changes and technological improvements make cost analysis a complicated process. On the other hand, current low commodity prices have put a greater emphasis on cost reduction and process optimization to ensure viability of mining projects. In this article, two material handling systems, a semimobile in-pit crusher and conveyor systems (IPCC) and traditional truck and shovel systems (TS), are compared through the cost analysis of an iron ore prefeasibility study. Furthermore, robustness of the design parameters is evaluated through a sensitivity analysis to determine the relative importance of project parameters. Finally, risks associated with uncertain design parameters affecting cost analysis are assessed through Monte Carlo simulation. The results indicated that IPCC is more cost effective than TS.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1080/0013791X.2016.1253810 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:uteexx:v:62:y:2017:i:4:p:369-386

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTEE20

DOI: 10.1080/0013791X.2016.1253810

Access Statistics for this article

The Engineering Economist is currently edited by Sarah Ryan

More articles in The Engineering Economist from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().