Selection of the most proper drilling and blasting pattern by using MADM methods (A case study: Sangan Iron Ore Mine, Iran)

  • Mohammad Javad Rahimdel Department of Mining Engineering, Faculty of Engineering, University of Birjand https://orcid.org/0000-0002-7980-6212
  • Ahmad Aryafar Department of Mining Engineering, Faculty of Engineering, University of Birjand
  • Ehsan Tavakkoli Department of Mining Engineering, Faculty of Engineering, University of Birjand
Keywords: Drilling and blasting pattern, Sangan Iron Ore Mine, AHP, TOPSIS, PROMETHEE

Abstract

Drilling is the first stage of open pit mining that has a considerable effect on the other stages of mining, including blasting, loading, hauling and crushing. An unsuitable drilling pattern may lead to undesirable results such as poor fragmentation, back break and fly rock that not only results in technical and safety issues but also increases the operating cost of the mine. Multi-Attribute Decision-Making (MADM) methods can be useful approaches to select the appropriate drilling pattern among various alternatives, performed previously. This paper aims to select the most proper drilling and blasting pattern for Sangan Iron Mine, Iran. To achieve this, in the first step, rock fragmentation, back break, fly rock, specific charge and specific drilling were considered as the decision criteria and their degree of importance was calculated using the AHP method under a fuzzy environment. Then, TOPSIS and PROMETHEE methods were used to select the most proper alternative. The results of this study show that the drilling pattern with a spacing of 5 m, burden 4 m, hole depth 10 m, and hole diameter 15 cm is the most suitable one. The stemming length and powder factor of the suggested pattern are 2.3 m and 2.6 gr/cm3, respectively.

Published
2020-06-22
How to Cite
Javad Rahimdel, M., Aryafar, A., & Tavakkoli, E. (2020). Selection of the most proper drilling and blasting pattern by using MADM methods (A case study: Sangan Iron Ore Mine, Iran). Rudarsko-geološko-Naftni Zbornik, 35(3). Retrieved from https://hrcak.srce.hr/ojs/index.php/rgn/article/view/10799
Section
Mining