Optimising for the future with ORB

 

ORB is a powerful optimisation tool that delivers significant value from strategic planning through to real-time equipment dispatch. With the addition of simulation functionality, ORB is able to test planning scenarios for robustness and investigate alternative strategies to evaluate performance in a virtual future. 

For instance, during the planning stage for a new or expanded mining operation, a simulation model can be used to predict ORB's future production performance and test different operational strategies. Development programs can also be tested for robustness by subjecting optimised ORB development schedules to variable task completion times and heading progress.

During production, once initialised using system data to represent the current mine state, a simulation model can also be used to simulate mine events such as drawpoint hang-ups and materials handling system outages to predict ORB performance for best to worse case scenarios providing forward visibility for production rates. It can also be used to test different strategies such as how much to mine an area before versus after a planned maintenance closure to maintain production.

Shift supervisors can anticipate tonnage totals for the day, several hours beforehand, or engineers can test a mine development schedule in detail to decide if the schedule will be complete before a prescribed deadline. Planning teams might gain visibility over the current capacity of their system, test the impact of increasing the speed of the materials handling system, or the effect of adding more loaders. 

Consider a draw strategy for a block caving operation and the potential for hang ups throughout production to impact the plan. Imagine being able to use historical drawpoint behaviour patterns to establish the likely performance range for the caving operation for the next 3 months. Or using ORB to evaluate alternative draw strategies to minimise the production impacts of a road panel closure planned for three-days-time. 

Using simulation increases preparedness for potential problems and performance variability, as well as creating visibility over the likely range of outcomes across a variety of time spectrums to assist with decisions today, tomorrow and in the future. 

For more information, or to book a demo, visit orb.polymathian.com

 
 

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