Evaluation of model uncertainty propagation in mineral process flowsheet designs

Abstract

Increasing demand for critical raw materials and energy transition metals sets new targets for the mineral processing, also resulting as higher requirements for the simulation tools during process design and optimization. This study presents a framework for global uncertainty evaluation of modelled plant-wide processes, where the propagation of uncertainty sources is addressed. The uncertainties exist, for example in operational and design parameters and in material properties. The approach was demonstrated with a typical mineral processing flowsheet simulated with commercial software. First, domain knowledge was adopted to screen the parameter space and then Monte Carlo simulation was performed. After this, the generated data set was used to identify surrogate models between the uncertain inputs and process performance indicators. Finally, a global sensitivity analysis was conducted to identify the effects of uncertainties to the decision-making in process design. The results were particularly used to locate the process points where accurate information is needed for the robust process design, or where on-line measurements would be preferred to establish on-line optimization.