Ripper Production Prediction for Laterite Excavation in Iron Ore Mines
Akhil Avchar1, Bhanwar S. Choudhary2
1College of Technology and Engineering, Udaipur, Rajasthan, 313001 India
2IIT (ISM), Dhanbad, 826001 India
Keywords: Iron ore mines, ripper dozer, production prediction, laterite
Abstract
The mining of iron ore, an essential raw material for iron and steel industry, is of prime importance among all mining activities undertaken by any country. Therefore it is important that the iron ore mining should be environment-friendly and sustainable. Ripper Dozer combination is one of the most commonly used excavation methods in Iron ore mines of Goa because of the presence of soft and friable rock mass and also it can bring the mining project more productivity, accuracy, safety and the additional option of selective mining. Improper selection of ripper dozer and unscientific deployment can lead to high production cost. So, performance prediction is an important issue for successful ripper application which deals with exposed rock mass properties and ripper machine parameters. Ripping production prediction using multiple linear regression analysis (MLR) and artificial neural network (ANN) is performed to estimate ripper production in the lateritic rock formation.
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