Abstract
Fouling of heat exchangers in the food industry results in frequent cleaning and an operational problem in scheduling production and cleaning periods. The complexity of the problem increases when a network involving more than one exchanger is involved, and requires a solution using integer programming techniques. A new modelling formulation has been developed to solve the resulting MINLP problem and provides near-optimal results. Application of the technique is illustrated with a case study of the raw juice preheat train in a sugar refinery featuring a network of 11 exchangers. Data reconciliation of plant information was used to generate linear fouling models for the simulation and the solver results are compared with current operating practice.
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