We’re working with Rio Tinto in Western Australia’s Pilbara region to maximise the throughput of their rail system by using simulations to balance train scheduling with maintenance and other system constraints.
Maximising supply chain efficiency is complex work
Rio Tinto manages over 1400 km of rail lines in the Pilbara in Western Australia, exporting over 225 million tonnes of iron ore every year from this region alone. This is worth billions of dollars to the Australian economy.
To ensure their supply chain runs at maximum efficiency they use medium term plans (ranging anywhere from two weeks to two years) to maximise throughput, identify bottlenecks in the supply chain, and schedule crews, production and maintenance of tracks and trains.
Simulate the scenario and automate the process
We developed a medium term planning optimisation tool in collaboration with Rio Tinto which has simplified and reduced the time and effort required for planning, by being able to easily simulate different scenarios.
Our models and algorithms find the optimal number of train services needed to maximise throughput, while observing system constraints such as port and rail maintenance requirements, the production plans at multiple mines, the capacity of each fleet, the grade and type of ore at each port and mine, and the shipping capacity of each port.
Our optimisation tool saves time and money
Our optimisation tool has reduced Rio Tinto’s planning times from five to six hours down to only one hour, and allowed them to better consider maintenance requirements by being able to generate simulation models for detailed scenario planning.
Our work has also formed the base model for their short-to-medium term maintenance planning, and has the potential to significantly improve throughput of the Pilbara supply chain.
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