A proposed approach for modelling competitiveness of new surface coal mines

Abstract

Cost estimation for surface coal mines is a critical practice that affects both profitability and competitiveness. New mines require these costs to be estimated using available information before a project begins. The competitive advantage of a new mine depends on it being both efficient and cost-effective. Low-cost producing mines have a higher chance of survival in a low-price environment than do high-cost producers. The competitiveness and profitability of a coal mine is based on the costs of production and the supply position on the cost curve. There is no single method of cost estimation, and the available methods consider only one or a few variables, leaving out multiple variables that could significantly affect the estimation of mine costs. Mining companies are thus searching extensively for a method that will increase accuracy in the estimation and evaluation of mining projects This paper highlights the shortcomings of the available approaches and proposes a data envelopment analysis method to develop a frontier for effective surface coal mines, and the use of a parametric method for modelling the costs and productivity of new mines to ensure effective competitiveness. The models will extend the capability of estimation and the accuracy of estimates using the efficient decision-making units, by considering the optimal mine-specific and external variables affecting costs.