Pilbara Iron Ore — Data Pipeline and Schedule Visualisation

Rio Tinto Iron Ore utilises a linear programming-based scheduling model to plan and integrate their iron ore operations in Western Australia.

Three primary challenges faced by the client were data preparation for scheduling, equipment modelling within the linear programming framework, and visualisation of the resultant schedules.

The existing process utilised various scripts, pivot tables and complex Excel spreadsheets to prepare the scheduling inventories. This was a time-consuming process with many interfaces which could lead to data errors.

Due to the size of the data set, the client required a method to clearly visualise the output of the schedule from the linear program model.

IMC Mining developed a streamlined data conversion process using the Python programming language to quickly translate a block model into the format required for scheduling and apply all relevant modifying factors. This significantly increased the reproducibility and transparency in the planning process and decreased data preparation time.

IMC utilised an in-house developed methodology for modelling trucking hours along a system of roads within a linear programming framework that led to significantly faster schedule solve times for the client's model.

IMC also developed its own in-house schedule visualisation solution based on Kitware Paraview that was tailored to the needs of the client.

The solution simultaneously visualised the development of multiple operations in a region over time, giving the planning team unprecedented insight into the spatial and temporal development of their operations.

Data preparation time was significantly reduced while improving auditability and reducing the risk of transcription errors.