Open-pit mines face a series of economical and practical problems when mining pits become deeper over various developmental stages. Rising strip ratio means that significantly more overburden material should be moved along with the ore. Deeper ramps mean greater time needed for hauling. The standard solution of merely adding new haul trucks is not effective enough. Extra trucks result in extra traffic jams on ramps, waiting at the shovels’ loading sites, as well as increased maintenance costs. Effective scheduling of the fleet needs mathematics and engineering solutions.
Conventional spreadsheet models fail to account for the complex non-linear nature of the maintenance costs associated with heavy-haul fleets. Equipment repair costs fluctuate significantly based on the number of truck operating hours and engine overhauls. Mixed integer program models allow scheduling the number of truck operating hours within different age groups over several years. Life of mine mathematical model lowers maintenance costs by 10% to 25% and maintains the achievement of annual production levels. Two-stage goal programming fleet management systems combine short-term production schedules with dynamic truck dispatching. The first optimization stage consists of allocating shovels at mining faces for grade requirements. At the second stage, trucks are dispatched to keep shovels running and production deviations below 4%.
Standard match factor formulae generally consider full equipment availability and constant arrival times, leading to a higher estimate of fleet efficiency compared to what mine planners achieve. Mining operations face mechanical breakdowns, variations in loading times, and cycle delays depending on travel routes. The expanded match factor includes a performance factor for equipment availability, travel speed, and rock fragmentation. For heterogeneous fleets where more than one type of trucks uses the same ramp, differences in travel speed lead to vehicle bunching since the speed on the ramp depends on the slower truck. Fragmentation, due to blasting, affects bucket fill factors and loading times. With the inclusion of operational downtime and fragmentation factors in the fleet size formulae, the effective match factor rises from 0.74 to 0.85.
As the open pit mining goes deeper, there is need to make some physical and technological improvements to maintain efficiency in hauling amid high stripping. The trolley assist system allows the diesel electric haul trucks to connect to the catenary line overhead wires during steep uphill sections. The electric connection increases the speed of the loaded uphill operation by about 10 kilometers per hour and decreases the use of diesel and engine overhauls. However, trolley assist system can only be used if there are stable ramps of at least 500 meters in length and should be in use for not less than two years. The mine designers will have to increase the width of haul road from the normal 38 meters to 51 meters for the 320 tonne trucks.
The problem of equipment scheduling in the light of increasing strip ratio cannot be solved simply through buying more haul trucks. There must be incorporation of mathematical optimization of the fleet, match factors, and infrastructural improvements. Multi-period goal programming and integer programming help achieve minimum maintenance costs but at the same time make it possible to stick to the production schedule. Long-term calculations of the match factor will avoid too much fleet turnover due to inclusion of the factors of mechanical time loss and fragmentation problems.
