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 utilizó datos disponibles públicamente, información de la industria y la amplia experiencia del cliente para modelar el complejo sistema gracias a RACE, nuestra herramienta patentada de apoyo a la toma de decisiones para cadenas de suministro basadas en ferrocarriles.

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.

The client has mathematically accurate insight into current and future capacities and constraints for their operations.

The client can now identify which operational improvements will result in the highest long-term value.

Contracts can consider the opportunities and limitations of the wider network for more reliable order fulfilment.