Data-Driven Autonomous Haulage Systems Simulation
Hooman Askari, University of Alberta; Mohammad Tabesh, Teck Resources Limited; Shiv Prakash Upadhyay, CNRL; Mohammad Mahdi Badiozamani, University of Alberta
We present a mine haulage simulation tool developed and implemented at for a large scale mining operations to assess the impact of autonomous haulage systems on mine productivity. The simulation model has been used as an operational planning tool in the client’s business. The simulation tool takes the mine production schedule as an input and imitates the truck-shovel haulage-systems and its interaction with the extraction plant including crushers and downstream assets. The simulation tool reported the major system’s KPIs at 95% level of statistical confidence within 3% accuracy of the historical dispatch data for the project. Major KPIs reported by the automated output reporting system are: ore and waste production, queue time, spot time, load time, dipper tonnage, haul time, dump time, truck speeds, backup time, loading cycle time, head grade, time and number of trucks in queue, and truck-and-shovel operational KPIs. The simulation tool gives the planner capability to assess the impact of changing operational scenarios such as stockpiling, different sizes of mixed-fleet trucks, and introduction of new haul-roads into to the mine plan. Results of the project will be presented.
Autonomous Haulage Systems
Discrete Event Simulation
Data Driven Simulation