Coal Blending: Business Value, Analysis, and Optimization

Abstract

Coal blending is a critically important process in the coal mining industry as it directly influences the number of product tonnes and the total revenue generated by a mine site. Coal blending represents a challenging and complex problem with numerous blending possibilities, multiple constraints and competing objectives. At many mine sites, blending decisions are made using heuristics that have been developed through experience or made by using computer assisted control algorithms or linear programming. While current blending procedures have achieved profitable outcomes in the past, they often result in a sub-optimal utilization of high quality coal. This sub-optimality has a considerable negative impact on mine site productivity as it can reduce the amount of lower quality ROM that is blended and sold. This article reviews the coal blending problem and discusses some of the difficult trade-offs and challenges that arise in trying to address this problem. We highlight some of the risks from making simplifying assumptions and the limitations of current software optimization systems. We conclude by explaining how the mining industry would significantly benefit from research and development into optimization algorithms and technologies that are better able to combine computer optimization algorithm capabilities with the important insights of engineers and quality control specialists.