Traditional sub-level caving (SLC) production scheduling models primarily focus on optimising draw control while overlooking the integration of post-extraction ore flow, including stockpiling and processing constraints. This omission can potentially lead to inefficiencies in ore blending, increased dilution, and suboptimal resource utilisation. To address this limitation, this study develops a mixed- integer programming (MIP) model that explicitly considers ore flow across the entire mining value chain. The proposed approach integrates a 3D block model, enabling more detailed constraint formulation and precise production sequencing compared to conventional 3D models. Furthermore, the model incorporates deleterious element constraints and stockpiling strategies, improving ore quality control and minimising contamination penalties. The model is implemented using the Gurobi optimiser and validated through a case study of an iron oxide copper-gold (IOCG) deposit. Results demonstrate that the proposed method enhances scheduling flexibility, increases mine operational efficiency, and improves ore quality management while maximising net present value (NPV).