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Stochastic optimisation provides a framework that is capable of generating a strategic life-of-mine production schedule that increases net present value while simultaneously reducing the risk associated with geological uncertainty. This paper focuses on the application of the stochastic strategic mine planning for technical risk management in the KéMag iron ore deposit in Quebec, Canada, demonstrating the key steps of the framework. The approach first quantifies both the volumetric and multi-element grade uncertainty of the deposit by generating a set of equally probable scenarios of the orebody. In this case study, the boundaries of the lithologies (volumetric uncertainty) defining the KéMag iron ore deposit are generated using a pattern-based wavelet simulation algorithm. The pertinent grade properties, namely, head iron, Davis Tube weight recovery, Davis Tube concentrate iron and silica content (multi-element grade uncertainty) are jointly simulated using the direct block minimum/maximum autocorrelation factors algorithm. Subsequently, the simulated scenarios of the iron deposit serve as an input to a life-of-mine stochastic integer programming production-scheduling model. The latter stochastic optimisation model is employed to manage and minimize the risk associated with the geological uncertainty of the deposit in terms of meeting production targets while generating a mining sequence of extraction maximising the net present value. The results of the case study quantify the risk associated with the product's silica content, total iron production and expected discounted annual cash flows. [ABSTRACT FROM AUTHOR]