Selected work

Case study / 04

Rail & Bulk Supply Chain Modelling

Operational decision support

A body of simulation and capacity work spanning mine, rail, port, logistics, and infrastructure planning.

Operational modelSystem boundary and decision outputs

A discrete-event model follows material and fleet through mine or source, stockpile and loadout, the rail network, port or plant unloading, and the empty return cycle. Schedules, maintenance, delays, infrastructure, operating rules and fleet availability influence the entire cycle. Outputs include throughput, utilisation, queues, cycle times, bottlenecks and scenario comparisons.

Model inputsConditions affecting the whole cycle
SchedulesMaintenanceStochastic delayInfrastructureOperating rulesFleet availability
Discrete-event simulation boundaryMine-to-destination operating cycle
01Mine / sourceMaterial release
02Stockpile / loadoutQueue · load · depart
03Rail fleet & networkTravel · meet · pass · wait
04Port / plantQueue · unload · release
Empty fleet return · network back to the next loading cycle

Shared state: queues · asset availability · fleet position · current events

Decision outputsCompare whole-system behaviour
ThroughputUtilisationQueuesCycle timesBottlenecksScenarios
Loaded movement runs to the destination; the empty fleet returns through the network to begin the next cycle.

01 / Operational question

The bottleneck moves

The capacity of a loadout, rail line or unloader does not predict the throughput of the whole operation. Fleet cycles, queues, train interactions, maintenance, stochastic delay and operating rules move the effective constraint from one part of the system to another.

The modelling task is to represent those dependencies at the level needed for a real planning decision, without burying the result in unnecessary detail.

02 / Model boundary

Follow the complete operating cycle

Discrete-event models follow material from mine or source through stockpile and loadout, across the rail network, into port or plant unloading, and then follow the empty fleet back into the next cycle.

Schedules, asset availability, maintenance windows, delay distributions, infrastructure limits and operating rules all change the same shared system state. That is what exposes queue formation, knock-on delay and constraints that isolated calculations miss.

  • Calibrated process and travel times
  • Explicit infrastructure, fleet and operating constraints
  • Controlled scenario changes against a common baseline

03 / Decision outputs

Compare the operation, not just a headline tonnage

Scenario runs report throughput alongside cycle times, utilisation, queues and bottlenecks. Together, those measures explain why a result changed and help distinguish a local improvement from a constraint shifted elsewhere in the chain.

04 / Representative work

Rail and bulk systems across several operating contexts

Public examples include Mineral Resources iron ore, Bowen Rail, Roy Hill, CBG bauxite, BHP Billiton iron ore, Aurizon coal, Queensland Rail bulk freight and Hunter Valley coal operations.

The Roy Hill rail operations platform was delivered over ten weeks, with partial functionality available after five. It combined mine and port delays, train scheduling, maintenance closures, infrastructure options and operational reporting in one simulation environment.