Document Type : Original Article
School of Mining Engineering, Amirkabir University of Technology, Tehran, Iran
Department of Industrial Engineering & Management Systems, AmirKabir University of Technology, Tehran, Iran
In the recent decade, very few studies have been done on mine reclamation cost estimation and no study has been conducted on proposing mine reclamation cost estimation models based on historical data. This study aims to develop predictor models for mine reclamation costs. To this end, after collecting the historical cost data of 41 open-pit mine reclamation projects, a comprehensive data set of 16 mine reclamation costs groups and the extent of the disturbed mined land corresponding to each group was prepared. Given the advantage of the regression method in developing a reliable predictor model with few data, the proposed cost models are developed based on the regression analysis technique. The R square for all and more than 87% of the developed models was more significant than 85% and 90%, respectively, indicating the proper fits on the data sets. Also, the root mean square error ratio to the standard deviation of observed cost data (RSR) was lower than 0.7 for all developed models, indicating the predictor models' good performance on reliably estimating mine reclamation costs. These efficient and simple general models can help make the right decisions by mine reclamation planners and pave the way to achieve sustainable mining by considering mine reclamation cost in the mine planning and design process.