Truck Allocation and Shovel-Truck Matching
Understanding cycle components, match factor, and how FMS systems balance trucks across shovels.
Optimising Shovel-Truck Fleet Matching
No mine runs in perfect balance for an entire shift. (This article refers to “shovels” throughout, but the same principles apply to excavators and loaders.) Shovels break down, trucks go to the workshop, operators take crib breaks, and faces change. An operation that starts the shift over-trucked at one shovel can be under-trucked at another within the hour. The job of truck allocation, deciding how many trucks work with each shovel and when to move them, is a constant balancing act, and it is one of the biggest levers an FMS gives you.
This is distinct from fleet sizing, which is the strategic question of what size trucks to buy and how many to own. Truck allocation is the operational question: given the trucks you have available right now, how do you distribute them across active shovels to meet production targets?
Why It Matters
When a shovel has too many trucks assigned, they queue. That is not just wasted fuel. Every truck sitting in a queue at an over-trucked shovel is a truck that could be getting loaded at a hanging shovel somewhere else. The opportunity cost is double: you pay for the idling truck and you lose production at the starved shovel.
When a shovel has too few trucks, it hangs. The shovel sits idle between loads waiting for the next truck to arrive. A single shovel costs more per operating hour than a single truck, so hang time is expensive. But that comparison is not as straightforward as it sounds. Five trucks idling in a queue potentially cost more than the shovel they are waiting for. The economics depend on the specific fleet.
The target is zero queue time. In practice that is hard to achieve, so most operations aim for less than a minute. If a truck arrives at the shovel when the currently loading truck is halfway through loading, that is a pretty good result. The arriving truck waits briefly, and the shovel transitions straight to the next load with minimal hang time.
Queue targets and bunching prevention are covered in detail in Queue Management and Truck Bunching.
Understanding the Cycle
Cycle time is measured dump-to-dump, not shovel-to-shovel. The cycle starts when a truck departs the dump empty and ends when it completes its next dump. A typical FMS breaks this into components:
- Travel Empty: empty haul from dump to shovel
- Queue at Load: waiting behind other trucks at the shovel
- Spot at Load: reversing into position under the shovel
- Loading: shovel filling the tray
- Travel Full: loaded haul from shovel to dump
- Queue at Dump: waiting at the dump point
- Spot at Dump: positioning to tip
- Dumping: tipping the load
The exact names vary between FMS vendors (“Queue at Dump” might be “Wait at Sink” in another system) but the concepts are the same.
The real value of breaking cycles into components is understanding how much time is spent in each part. When you track these over time, you see variances. Maybe travel empty times on Route 3 have crept up 40 seconds over the last week. That tells you something about road condition. Maybe queue times at Shovel B spike every afternoon. That points to an allocation imbalance after lunch breaks. Identifying which component is changing tells you where to investigate and what to fix.
What Inflates Fleet Requirements
Three things eat into your effective fleet, and they work differently.
Delays are short-duration cycle interruptions: waiting at intersections, right-of-way pauses, brief stops for light vehicles. Delays inflate individual cycle times but the truck stays in the fleet.
Standbys are planned non-productive time: refuelling, personal breaks, crib breaks, shift changeover. Standbys reduce the effective operating hours in a shift. A truck on standby is not broken, but it is not hauling either.
Downs (breakdowns) take the truck out of the fleet entirely. A truck in the workshop does not exist for allocation purposes.
On top of these, micro influences (traffic congestion on single-lane haul roads, poor road conditions after rain, congestion at fuel bays) leave traces in your cycle data even when they are not captured as formal timecodes. They show up as creeping travel times or unexplained variance.
The distinction matters because each requires a different response. Delays are addressed through cycle time analysis and operational fixes. Standbys are managed through shift scheduling and break coordination. Downs are an availability and maintenance problem.
Key Definitions
| Term | Definition | Unit |
|---|---|---|
| Payload | Mass of material loaded in the truck tray | tonnes |
| Nominal payload | Predetermined payload based on truck model and tray size | tonnes |
| Cycle time | Total time from dump departure to next dump completion | minutes |
| Loading time (Ts) | Time the shovel actively loads one truck (loading only, not queue or spot) | minutes |
| Truck productivity | Payload divided by cycle time | tonnes per hour |
| Shovel productivity | Total tonnes loaded per hour across all trucks | tonnes per hour |
A common mistake is defining payload as “the product of cycle time and load per cycle.” That conflates payload with productivity. Payload is just the mass in the tray. Productivity is payload divided by cycle time, how many tonnes per hour each truck delivers.
Match Factor
Match factor is an established metric in mining engineering for checking whether truck allocation is in the right ballpark (Burt & Caccetta 2007). It is not the only number that matters, but it is a quick sanity check that most mines use.
MF = (N x Ts) / Tc
Where:
- N = number of trucks assigned to the shovel
- Ts = shovel service time (loading time only, the time the shovel actively loads one truck)
- Tc = total truck cycle time (dump-to-dump)
| MF Value | Meaning | What You See |
|---|---|---|
| MF = 1.0 | Perfect balance | Shovel finishes loading, next truck is immediately ready |
| MF < 1.0 | Under-trucked | Shovel has hang time waiting for trucks |
| MF > 1.0 | Over-trucked | Trucks queue at the shovel |
Most mines target a match factor between 0.85 and 1.0. Running at exactly 1.0 is theoretically perfect but fragile. Any variability tips you into queuing or shovel idle time. In practice, a large number of operations deliberately run slightly under-trucked. The logic is straightforward: a small amount of shovel hang time is cheaper and easier to manage than a fleet of trucks burning fuel in queues. Running at MF 0.85 to 0.95 gives you a margin to absorb variability without trucks stacking up.
But match factor is a snapshot. It tells you the balance at a point in time with a specific truck count and cycle time. When a truck goes down mid-shift, your MF drops. When operators return from breaks and an extra truck comes back online, it rises. The number shifts constantly, which is why FMS systems recalculate allocation continuously rather than setting it once at the start of shift.
Worked Example
A shovel loads each truck in 3.5 minutes (Ts = 3.5). The full truck cycle time is 28 minutes (Tc = 28). You have 7 trucks assigned (N = 7).
MF = (7 x 3.5) / 28 = 24.5 / 28 = 0.875
This shovel is under-trucked. It will experience some hang time between loads. To reach MF = 1.0, you would need Tc / Ts = 28 / 3.5 = 8 trucks. Whether you pull a truck from another shovel to fill that gap depends on what the other shovel’s match factor looks like, and whether you can afford to under-truck it instead.
Truck Count Methods
When planning how many trucks a shovel needs, two methods are commonly used. Both should converge with consistent inputs.
Method 1: Cycle Ratio
Raw truck count = Tc / (Ts + Spot time)
Divide the total cycle time by the time the shovel spends serving one truck (loading plus spotting). Then reduce by roughly 10% for practical efficiency, a common default, though it depends on how much hang time your operation can tolerate.
Example: Tc = 28 min, Ts = 3.5 min, spot time = 1 min.
Raw count = 28 / (3.5 + 1) = 28 / 4.5 = 6.2 trucks
With 10% efficiency factor: 6.2 x 0.9 = 5.6, so 6 trucks.
Method 2: Throughput
Start from the production target and work backwards.
Trucks needed = Shovel target (tph) / Truck productivity (tph per truck)
Example: Shovel target = 3,000 tph. Each truck carries 220 tonnes with a 28-minute cycle.
Truck productivity = 220 x (60 / 28) = 220 x 2.14 = 471 tph per truck
Trucks needed = 3,000 / 471 = 6.4, so 7 trucks.
Buffering for Reality
Both methods give you the theoretical minimum. Real operations need a buffer.
A buffer of 1.2 to 1.3 times the theoretical minimum accounts for:
- Breakdowns: trucks in the workshop reduce your available fleet
- Delays and standbys: refuelling, personal breaks, shift changeover
- Cycle time variability: traffic congestion, road conditions, single-lane haul roads
Equipment Pairing
Truck allocation assumes the trucks are the right size for the shovels in the first place. That is the fleet sizing question, a planning decision made when selecting equipment.
The rule of thumb is that a shovel should fill a truck in 2 to 4 minutes for well-matched electric rope shovels and ultra-class trucks, typically in 3 to 5 passes. Loading times outside this range usually indicate a mismatch. Either the bucket is too small for the truck (too many passes, shovel wears out faster) or too large (overfilling risk, payload variance).
Mismatched equipment is common on sites with mixed fleets. Some operations run different truck sizes assigned to different shovels. Others accept imperfect matching with a single truck class. The simplicity of one fleet type often outweighs the efficiency gain of perfect matching.
Dynamic Rebalancing
Static truck assignments (“these 7 trucks work with Shovel A all shift”) only work when nothing changes. In practice, conditions change constantly. Shovels go down, trucks break, operators take breaks, faces change, and production priorities shift mid-shift. The balance at any given shovel can flip within the hour.
FMS systems handle this through dynamic rebalancing, also called dynamic dispatch, unlocked allocation, or auto assignment depending on the vendor. The concept is the same regardless of the marketing label: trucks are reassigned at different points across shovels based on current conditions. When a shovel goes down, its trucks are immediately redistributed. When a shovel’s queue builds, the system holds back inbound trucks and redirects them to hanging shovels elsewhere.
Dynamic rebalancing improves both utilisation and productivity, and these are not the same thing. Utilisation is the ratio of productive time to available time. Productivity is the output rate in tonnes per hour. A truck can be highly utilised (always moving) but unproductive (hauling short loads on long routes). Good rebalancing optimises both.
The mechanics of dynamic versus static dispatch are covered in Static vs Dynamic Dispatch Strategies.
Parking Equipment
Sometimes the maths says you have more trucks than you need. Parking a truck (taking it out of the active fleet) is a valid decision, but it should be a last resort. Before you park anything, pull the other levers first: adjust haul routes to lengthen or shorten cycles, coordinate refuelling to stagger truck availability, bring forward operator breaks to thin out the fleet temporarily. If the imbalance persists after those adjustments, then park. Keeping a truck running just to keep it moving wastes fuel and creates unnecessary queue time at shovels that are already adequately served.
Key Takeaways
- Truck allocation is dynamic, not static. Operations shift between over-trucked and under-trucked throughout a shift. There is no set-and-forget fleet balance.
- Cycle time is dump-to-dump. Break it into components and track variances. The component that is changing tells you where the problem is.
- Match factor is a sanity check, not gospel. MF = (N x Ts) / Tc. Target 0.85 to 1.0, but remember it shifts constantly as conditions change.
- Queuing trucks have an opportunity cost. Every truck idling at an over-trucked shovel is a truck that could be getting loaded at a hanging shovel.
- Buffer for reality. Plan for 1.2 to 1.3 times the theoretical truck count to cover breakdowns, standbys, and cycle time variability.