A Coupled Expert System Approach To Blast Optimization And Fragmentation Modeling

The need for an integrated approach to optimization of unit operations in both the pit and the mill has long been recognized, but the complexity and nature of the overall problem has up to now resisted solution. This paper reports on a modeling methodology which couples symbolic and numeric computing to unify operations in both the pit and mill. The ultimate goal of this work is to optimize all operations that are influenced by blasting. Blasting plays a key role in all facets of operations. Obviously, drilling and blasting costs are determined by blast design, but the down-stream costs that are closely related to blasting results are often treated as separate functions: loading, hauling, cleanup, and crushing and grinding are all heavily influenced. Diggablilty and bucket fill factor are a function of fragmentation, the condition of the floor and uniformity in the shape of the muck pile. Likewise, cycle times and loading delays partially determine haul cycles, while fragmentation distribution and size determines the efficiency of truck loading. Removal and breakage of oversize causes loading delays and increases cleanup costs. The influence of blasting doesn't stop at the crusher. Mill productivity, power consumption, and maintenance are a function of the feed. Even at the SAG mill a reduction of a critical particle size during blasting can increase throughput. Thus, a bottle-neck for production far removed from unit operations in the pit can be alleviated by a modification in blast design. The question is: how do we optimize blasting with respect not only to itself but to al\ related mining and milling operations? For that matter, how do we even model blasting so that we can control the results of a blast?