Development of mine operation value chain flowsheets fine-tuned and constraint based on the process information (PI) data to evaluate proposed operation strategies and ore pre-treatment technologies

Application of ore pre-treatment technologies such as Grade Engineering and in-pit ore treatment require comprehensive analysis to show proven value is being generated by switching away from the current practices. Considering most mining operations last several decades; the pre-treatment technologies must be investigated over life of mine (LOM) to truly show value was generated or lost. Therefore, a value chain flowsheet model has been usually developed to run those analysis/simulations over LOM using a set of defined ore characteristics and the operating equipment capacities. The Integrated Extraction Simulator (IES) has been used for this type of LOM simulations as it has the necessary flexibility to accommodate the whole mining value chain flowsheet in one platform and provide essential computation power to run mass simulations for the given scenarios using the resource block model. This allows to forecast the value chain response over the LOM for all given scenarios in a feasible amount of time. The traditionally developed flowsheets for the analysis/simulations are usually limited to the mineral processing plant and were developed based on a single audit conducted on the plant in a very short time, e.g. several hours. The process plant is being operated with a certain ore at a certain condition during the short audits which would not reveal the true capacity of the operation equipment when ore characteristics changes. Therefore, it would be impossible to define the true capacity of the equipment and identify the constraints along the value chain. In this study, a methodology was developed to identify the constraints along the value chain and implement those in the IES flowsheet using process information. Also, the equipment models were fine-tuned to represent the true capacity of the equipment in the flowsheet using the same data set. The methodology was tested over five process plant in two operations and showed the performance forecast was significantly improved over the traditional methods being used so far. Then those high-fidelity flowsheets were used to evaluate the ore pre-treatment technologies proposed by the relevant resource company experts.