The customer is a coal mining company which operates a mining complex in central Queensland.
The client was in the process of increasing their product output through a series of de-bottlenecking exercises for their underground operations. They were also planning upgrades to increase the capacity of their coal handling preparation plant (CHPP) and the efficiency of their train load-out (TLO).
The client’s mines operate within a system where multiple producers share rail infrastructure and depend on the same haulage providers to transport coal from their TLOs to export terminals. Before investing heavily in infrastructure improvements, the client needed to be certain that the greater network would be able to handle expected increases in output.
Polymathian used publicly available data, industry information, and the customer’s extensive experience to model the complex system using RACE, our proprietary decision support tool for rail-based supply chains.
Multiple scenarios, such as different TLO configurations and impact of external factors, were then tested within this simulated system revealing the changes and upgrades that would pay off in the real world. By the end of the six-week project, a year’s worth of cloud computation time had been used to analyse the client’s operations under many alternative scenarios.
Educated guesses and industry estimates have been quantified and verified using data-driven analysis.Full system overview
The client has mathematically accurate insight into current and future capacities and constraints for their operations.Strategic planning
The client can now identify which operational improvements will result in the highest long-term value.Improved service levels
Contracts can consider the opportunities and limitations of the wider network for more reliable order fulfilment.