Blending decisions impact the total tonnes of each product that a mine site is able to sell. In addition, the quality attributes of a product can impact the final sale value of the product. Because blending has a significant impact on mine site revenue, several decision support systems have been developed with the aim of improving product reliability and profitability.
Blend optimization Blend optimization is a
nonlinear combinatorial optimization problem where the
objective is typically to maximize revenue,
Net Present Value (NPV), or monthly product tonnage targets. Important features of the blending problem include: • Each product may consist of many unblended seams or plys (
many to 1 mapping) and each seam or ply can contribute to multiple products (1 to many mapping). • Some products constitute a “brand” which cannot consist of blends with significantly different physical and chemical quality attributes. • Product sale value can change over time due to changing market conditions. • Sufficiently large scale production sizes can influence market fundamentals and thus sale price. • Operating costs are influenced by production rate and it is generally desirable to meet a specified operating capacity for the wash plant as well as to utilize contractual haulage, rail, and shipping capacities. Several constraints must also be taken into account including: • maximum number of
ROM types within a blend • minimum tonnage of given ROM type within a blend • maximum number of field stocks from which materials can be blended from ==Blend Analysis==