Real time optimization of the sterilization process in a canning industry

Sterilization process is aimed to inactivate potentially harmful microorganisms. To that purpose the packaged food is subject to a time/temperature profile. In the canning industry such profiles are chosen based on the experience of the operator. In the presence of perturbations, such as steam supply problems, operators must react and design new profiles which, in most of the cases, are too conservative and/or may lead to the batch rejection, either because of quality or safety reasons. In order to overcome this problem, we propose in this work a model based real time optimization (RTO) strategy. The model, which describes the different relevant aspects of the plant (retort/can temperature, color dynamics, microorganism lethality, energy consumption, etc.) is used to predict the behavior of the system. Plant measurements are taken periodically and, in the event of a perturbation, an optimization procedure is run to compute a new time/temperature profile based on the past measurements.