Grinding mill performance is typically controlled by making operating adjustments and taking external measurements to infer what is happening inside the mill. So optimising existing machines or designing new ones is difficult and expensive. DEM now offers a broad range of capabilities to look inside these mills to gain improved understanding of charge dynamics, prediction of the power draw and knowledge of the energy utilisation. In this paper, we demonstrate these capabilities of DEM for machine design by exploring the performance variations in a HICOM mill with changing operating conditions (such as fill level and mill speed) and different material properties (such as particle size, density and friction). These predictions compare well with existing experimental observations and provide new insights into the flow dynamics inside the HICOM mill. Together they demonstrate how the DEM method can be used in a mill optimisation or design process. Crown Copyright (C) 2016 Published by Elsevier B.V. All rights reserved.