Skip to content

HaulMax

Haul truck and shovel fleet optimization for surface mining operations.

HaulMax is the MineMax application for optimizing mine haulage. It models the load-and-haul cycle in detail, identifies sources of productive-hour loss, and recommends dispatch and routing changes that move tonnes more efficiently.

Public page coming soon

HaulMax is being added to the public ntwist.com mining solutions menu. This documentation describes the application as it operates in active customer deployments today.

What it does

  • Models the haulage network end to end: queue, spot, load, haul, dump, return, and refuel.
  • Identifies the systemic causes of unrecovered productive hours, not just point events.
  • Recommends shift- and day-level changes to truck and shovel allocation against current targets.
  • Quantifies the impact of alternative fleet, route, and refuel strategies before they are committed.

What's broken today

The haulage fleet is the single largest operating cost. In a typical surface mine, it is also the largest source of unrecovered productive hours: queueing, idle, partially loaded, refuel detours.

Dispatch optimizes for the next assignment. Most dispatch systems route trucks one decision at a time, without visibility into systemic causes of cycle-time loss across the shift.

The bottleneck moves. The constraint at 06:00 (shovel) is not the constraint at 18:00 (refuel queue). Without a model of the full cycle, operations chase the wrong fix.

How HaulMax works

Inputs. HaulMax works with data you already have:

  • Fleet management system (FMS) records: cycle times, truck and shovel assignments, location pings
  • Dispatch system data: assignment events, queue positions
  • Fuel system data: fuel events, refuel queue times
  • Equipment availability and maintenance signals
  • Mine plan and short-term schedule

Intelligence. HaulMax builds a calibrated LASL (load and shovel logistics) model of the haulage network and decomposes every cycle into productive, semi-productive, and unproductive time. It quantifies where time is lost across the full fleet, not just at the unit level.

Outputs. What users receive:

  • Shift-level dispatch advisories against current targets
  • Bottleneck analysis (shovel, haul, dump, refuel) with quantified hours of impact
  • What-if scenario tool for testing alternative fleet, route, and refuel strategies
  • Reconciliation reports on plan adherence and bottleneck movement over time

Deployment workflow

  1. Configure the haulage network: routes, segments, dump points, fuel stations, equipment classes.
  2. Connect FMS, dispatch, and fuel system data sources.
  3. Calibrate the LASL model against the last 30 to 90 days of cycle data.
  4. Baseline current productive hour distribution per truck, shovel, and route.
  5. Run what-if scenarios against the calibrated model.
  6. Deploy shift-level advisories to dispatchers and supervisors.

Top KPIs impacted

KPI Outcome
Truck productive hours per shift 3 to 8 percent uplift
Queue time at shovel 15 to 30 percent reduction
Tonnes moved per fleet-hour 2 to 6 percent uplift
Time to identify a new bottleneck Days to hours

Actual results depend on dispatch system maturity, data quality, and the degree of operational change accepted from the recommendations.

Industry focus

HaulMax is currently deployed against surface mining haulage, with primary use in oil sands operations. The underlying LASL model framework is generalizable; extensions to other surface mining contexts are roadmapped.

How HaulMax relates to other MineMax applications

HaulMax operates upstream of the mill, on the haulage network itself. It is deployed alongside DynaMax, which manages the ROM pad and short-interval feed downstream of haulage. OreMax and PlanMax provide the longer-horizon stockpile and blending context.

Primary users

Mine Dispatchers, Shift Supervisors, Mine Operations Manager, Fleet Engineering, Continuous Improvement.