Inferential estimation of viscosity index on a lubricant production plant

This paper presents an industrial case study examining the application of inferential estimation to a lubricant production plant. Three estimation algorithms are studied. First, an existing plant inference model is compared to a static estimator designed using information obtained from plant experiments. Next, the case for a dynamic and adaptive algorithm is presented. The procedures required to initialise the adaptive estimator are described, and implementation issues are discussed. This paper demonstrates that (provided such issues are carefully considered) an adaptive inferential measurement algorithm may be used to provide timely and accurate inferences.