The processing plant had three major types of mineralisation and was looking for a way to model the behaviour and optimise output.
Our client’s plant has three distinct types of mineralised zones that were presented to the processing plant. Each of these zones have distinct requirements for processing and varying impacts on recovery and throughput. At any time the processing plant will be running a mix of these three mineralisations. The impact of these zones is not linear across the feed ratios. A solution was needed to be able to predict the expected result from any given mineralisation ratio that the plant was likely to work in. This information would also allow blend optimisation based on the available stocks of feed material.
Interlate applied a differentiated suite of technology and analytical solutions that could be implemented quickly to materially improve productivity, with little or no additional capital expenditure.
Using existing plant data, Interlate working longside the site team, was able to create a user interface. When combined with subject matter expertise and the operating context, this user interface allows rapid identification of predicted operating conditions based on current feed conditions, and visual indication of the current versus predicted operation conditions.
Interlate used analytics, visualisation and subject matter expertise to identify productivity opportunities. This has allowed rapid identification of incoming ore related issues, and identification of where troubleshooting resources need to be utilised.