1636 Stage 3 of the process involved the construction of a cost model in Excel. This model defined both OPEX and CAPEX across all applicable mining methods and processing streams, incorporating key variables such as recovery, dilution, mass rejection and adjustment factors for depth and processing complexity. It also introduced parameters for partial utilisation and opportunity cost, capturing underperformance risk. By applying cost adjustment factors the model dynamically calibrated costs across mining depths and scenarios, enabling more realistic financial forecasting for IPM deployments. This stage included four key components 1. Stope modelling - develop a block model and define stopes based on the minimum cut-off grade, with multiple stope scenarios and pillar configurations tested. Stopes were oriented, designed and optimised by level to generate mineable units that reflected the geometry and grade distribution of the orebody. These stopes were then concatenated into a stope model that formed the basis for subsequent scheduling and economic assessment. This component provided the physical mining units used to evaluate conventional mining and IPM alternatives. 2. Operational constraints definition - define sequencing and stoping constraints and infrastructure requirements. This component consisted of setting the technical input parameters required for scheduling the CM and ILR pathways. 3. Business value driver creation - estimate CAPEX and OPEX, set the upper and lower boundaries for technical parameters. These inputs included mining, processing and development assumptions, as well as recovery, dilution, mass rejection and other technical performance factors relevant to each alternative. Once defined, these parameters were used to generate preliminary schedules for the CM and ILR streams. 4. Objective function description – compose time-based models to relate Net Present Value (NPV), Net Recoverable Metal Value (NRMV) or other key performance indicators to the inputs provided from 1 to 3 above over the scheduling horizon. Stage 4 transitioned into scheduling optimisation. In this study the objective was to maximise NPV over the mine life. Using the mathematical programming model created in Stage 3, the simulation allocated stopes to specific extraction routes (CM or ILR), sequenced development levels and scheduled backfilling and IMR to maintain geotechnical stability and enable continuous operation. The outputs from the CM/ILR scheduling step were used as inputs for IMR scheduling, allowing selected lower-grade, fragmented or residual material streams to be assessed for IMR. At this stage, additional economic parameters and recovery assumptions were incorporated, and the model evaluated how IMR would interact with the previously scheduled mining and processing streams. The final step was financial evaluation and analysis. The outputs from the CM, ILR and IMR scheduling steps were combined into a final production and processing profile, which was then used for economic assessment. The financial model evaluated the relative performance of each configuration using NPV and other operating indicators, allowing comparison between the conventional baseline and hybrid IPM scenarios. This model captured not only revenue and cost streams, but also infrastructure, fill and timing constraints, ensuring that mining and processing activities aligned with physical, technical and operational realities. The integrated simulation model offered a powerful framework for strategic mine planning, combining rigorous economic analysis with operational realism. By combining these steps, the framework could evaluate how the integration of ILR and IMR affected mine sequencing, processing capacity, material handling and economic performance under a common modelling structure. 2.3 Model assumptions and limitations To simplify the modelling the following technical assumptions are typically made: • The processing system must be sufficiently robust and capable of treating variable feed grades and
RkJQdWJsaXNoZXIy MTM0Mzk2