This work deals with the problem of resource efficiency monitoring in a multiple-effect evaporation process. The approach considers first a grey-box nonlinear stationary model of the process and data reconciliation methods to compute efficiency indicators and to update such model if necessary. The updated model is used in a real-time optimisation layer to compute operation points of the process. Then, some patterns for optimal operation have been identified and implemented by a self-optimising controller to drive the process. In a second step, the fouling, which reduce the heat-transfer efficiency in heat exchangers, is also considered as a function of time and control decisions, in order to optimally drive the process considering the long-term effect. This fouling behaviour forces periodic stops for cleaning, which will be also object of optimisation. Finally, the overall problem is formulated as a real-time optimisation to search for the optimal decisions during a whole operation cycle. (C) 2017 The Authors. Published by Elsevier Ltd.