| Abstract
| - In industrial processes, the potential benefit that arises from improved control is assessed before the installationof a new control strategy. Estimating the economic benefit motivates the investment in a new control systemand minimizes the risk of the new technology not living up to its promises. In this paper, a method for apriori estimation of the benefit from improved process control is presented. The method builds on conventionalestimation techniques and evaluates the performance function associated with the controlled variable byassuming a reduction in variance. Three frequently used performance functions, namely, a quadratic performancefunction, a linear performance function with constraints, and the so-called clifftent performance function, areinvestigated. The profit index as a function of the variance is computed, and the implications of a reductionin variance for each performance function are assessed. A further contribution of this article is the analyticalderivation of the optimal operating point of the controlled variable for a given performance function and agiven variance. The estimated benefit from process control originates from a reduction in variance. Severalapproaches have been proposed to estimate and assess the variance reduction. Here, an index for the assessmentof the current economic benefit incorporates the minimum achievable variance to estimate the reduction invariance. The economic benefit resulting from process control and the online monitoring index are demonstratedon an industrial refining process.
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