Mining is an important industry in Australia, contributing billions of dollars to the economy. The performance of a processing plant has a large impact on the profitability of a mining operation, yet plant design decisions are typically guided more by intuition and experience than by analysis. In this paper, we motivate the use of an evolutionary algorithm to aid in the design of such plants. We formalise plant design in terms suitable for application in a multi-objective evolutionary algorithm and create a simulation to assess the performance of candidate solutions. Results show the effectiveness of this approach with our algorithm producing designs superior to those used in practice today, promising significant financial benefits.