Optimization of shovel-truck system for surface mining

Erçelebi S. G., Bascetin A.

JOURNAL OF THE SOUTHERN AFRICAN INSTITUTE OF MINING AND METALLURGY, cilt.109, sa.7, ss.433-439, 2009 (SCI-Expanded) identifier identifier

Özet

In surface mining operations, truck haulage is the largest item in the operating costs, constituting 50 to 60% of the total. in order to reduce this cost, it is necessary to allocate and dispatch the trucks efficiently. This paper describes shovel and truck operation models and optimization approaches for the allocation and dispatching of trucks under various operating conditions. Closed queuing network theory is employed for the allocation of trucks and linear programming for the purpose of truck dispatching to shovels. A case study was applied for the Orhaneli open Pit Coal Mine in Turkey. This approach would provide the capability of estimating system performance measures (mine throughput, mean number of trucks, mean waiting time, etc.) for planning purposes when the truck fleet is composed of identical trucks. A computational study is presented to show how choosing the optimum number of trucks and optimum dispatching policy affect the cost of moving material in a truck-shovel system.

 In surface mining operations, truck haulage is the largest item in the operating costs, constituting 50 to 60% of the total. in order to reduce this cost, it is necessary to allocate and dispatch the trucks efficiently. This paper describes shovel and truck operation models and optimization approaches for the allocation and dispatching of trucks under various operating conditions. Closed queuing network theory is employed for the allocation of trucks and linear programming for the purpose of truck dispatching to shovels. A case study was applied for the Orhaneli open Pit Coal Mine in Turkey. This approach would provide the capability of estimating system performance measures (mine throughput, mean number of trucks, mean waiting time, etc.) for planning purposes when the truck fleet is composed of identical trucks. A computational study is presented to show how choosing the optimum number of trucks and optimum dispatching policy affect the cost of moving material in a truck-shovel system.