Results analysis for real-time optimization (RTO): Deciding when to change the plant operation

After the automation goals of safety, product quality and production rate have been achieved, opportunity exists in many plants to further increase profit by adjusting selected operating variables. When external conditions change frequently, incentive exists for the optimization to be performed in real time. However, real-time optimization might change conditions too frequently when responding to measurement noise and high frequency stationary disturbances. A results analysis method is proposed to decide when a significant change in plant operation has been proposed and should be implemented. The method is based on a knowledge of the common cause measurement variability and the transmission of this variability in the RTO loop to the recommended operating conditions. The basic expressions for the results analysis method are developed, and sample results from a case study are presented. Extensions are also briefly discussed.