Previous developments in the simulation of metallurgical operations led to the representation of alternating modes of operation. These operating modes are initially described as mass balances within a system of nodes, representing the components of the metallurgical plant, to a higher or lower degree of resolution, depending on the data available, and the objective of the simulation. As an engineering project progresses, the modes are represented in increasing levels of detail, focusing on the most critical aspects, i.e., the critical opportunities driving a project forward, and also the critical risks and threats that are obstructing progress. Whereas a high-level representation considers dynamic mass balances, and the fluctuating material contents of reactors (grinding mills, flotation cells, thickeners, etc., in the case of mineral concentrators, or furnaces and ladles in the case of smelters), a detailed representation may eventually benefit from immersive experiences, within a computer-powered virtual reality (VR) representation of the plant. The data generated by operators and engineers in VR can inform continuous improvement and reengineering projects for existing plants, as well as the later stages of a greenfield project (detailed engineering and ramp-up). Furthermore, VR representation of metallurgical plants is of pedagogical value for engineering students, likely impacting how future metallurgical engineers will execute their projects. The current paper presents the progress and feedback from a VR development of a fictitious concentrator and describes how these efforts could be merged with the simulation testing of machine-learning-enabled control systems and other emerging challenges in mineral processing and extractive metallurgy.