Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/3073
Appears in Collections:Management, Work and Organisation Conference Papers and Proceedings
Peer Review Status: Refereed
Author(s): Oraee, Kazem
Basiri, Mohammad Houssain
Sajidan, M H
Hayati, M
Contact Email: sko1@stir.ac.uk
Title: Risk Assessment in Block Cave Mining
Citation: Oraee K, Basiri MH, Sajidan MH & Hayati M (2011) Risk Assessment in Block Cave Mining. In: SME Annual Meeting & Exhibit and CMA 113th National Western Mining Conference 2011. 2011 SME Annual Meeting & Exhibit and CMA 113th National Western Mining Conference "Shaping a Strong Future Through Mining", Denver, Colorado, USA, 27.02.2011-02.03.2011. Dearborn, MI: Society for Mining, Metallurgy & Exploration, pp. 331-335.
Issue Date: 2011
Date Deposited: 14-Jun-2011
Conference Name: 2011 SME Annual Meeting & Exhibit and CMA 113th National Western Mining Conference "Shaping a Strong Future Through Mining"
Conference Dates: 2011-02-27 - 2011-03-02
Conference Location: Denver, Colorado, USA
Abstract: Mining Ventures are considered as high risk projects and therefore managing the risks is inevitable. Risk assessment is an important part of the complex process of risk management, hence applying appropriated and practical methods for ranking the risks associated with projects, can help to perform a better risk management. In this research the applicability of using Techniques for Order Preference by Similarity to Ideal Solution (TOPSIS) method for risk ranking in an underground mine, extracting by block caving method, was studied. Via this method, the risk associated with reserve estimation ranked as the first while in conventional method (P-I Matrix method) located in the sixteenth. Also there were significant differences in ranks of the other risks. Considering the more criteria, with different weights, in comparison with conventional methods, the results comprised from TOPSIS method are more reliable. By implementing this method risks are ranked better and more realistic and consequently then will be managed more efficient.
Status: VoR - Version of Record
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