Online decision support for an evaporation network

Abstract

This work presents a decision-support tool to address the model-based optimization approach for online load allocation and scheduling of cleaning operations in an evaporation network. The aim is improving the resource efficiency by supplying the optimal solution for a given production goal. The approach includes the semi-automatic update of evaporator models, which is based on historical data for minimal modelling effort. The structure of the problem is formulated via mixed-integer programming and integrated into the plant supervision systems. Production constraints, concerns about the practical implementation and visualization preferences are also taken into account in the design of the prototypical tool.