Pinto (1998) showed that an economical value might be assigned to model parameter uncertainties, which could be used for process optimization and for taking decisions during sequential experimental designs. The procedure is extended to take into account the fact that plant operation conditions change with time, leading to improvements of the plant operation and allowing the partial recovering of losses introduced by uncertain parameters during plant design. It is shown that the use of EVOP (Evolutionary Operation Procedures) during plant operation may reduce the cost of parameter uncertainties, exerting a major impact on process optimization and optimal design of experiments.