Open Cut » Overburden Removal
This project has developed a computer-based system for the study, design and optimisation of truck-and-shovel overburden removal. It includes functionality to allow the quick and approximate modelling of long term dragline spoil and incorporation of truck and shovel pre strip.
The researchers have been able to demonstrate the use of the system for user assisted optimising of a variety of objectives, across a number of pits and utilizing both fixed and variable fleets and have demonstrated the incorporation of various constraints including topographic, fleet, scheduling and ramp/access constraints.
The developed system has been successfully calibrated using truck and loader monitor data. The project has been able to demonstrate that the truck and loader models, when well calibrated, are capable of very accurate predictions of truck dynamics and overall productivity.
The output of the system includes:
· Block reserves model of volumetric data for the excavations and dumps;
· Material transport table detailing material volumes, source and destination;
· Productivity data; and
· A simulation slide show.
The case studies in this report cover short medium and long term examples. These studies demonstrated the use of the system in various modes ranging from quick and approximate methods to highly detailed simulations. Various excavation and dump sequences, dump locations and ramp/road configurations have been studied in the sample mines. Simulation output clearly identifies the productivity and scheduling consequences of these various options.
The dragline spoil module allows the rapid approximate modelling of dragline spoil piles in accordance with the long term plan. The system established a dragline spoil model, pre-strip horizon, coal, dragline waste and pre strip waste volumes. A set of tools has been developed to allow the rapid design of a benched landform to accommodate pre strip spoil within the dragline spoil and ramp footprints. Once this design is complete it can be subject to truck and shovel productivity modelling.