Data reconciliation — Progress and challenges

Measurements in a chemical process are subject to errors, both random and systematic, so that the laws of conservation of mass and energy are not obeyed. In order to record the performance of the process, these measurements are adjusted in order that they conform to the conservation laws and any other constraints imposed upon them. This procedure is known as data reconciliation. Advances in the theory and application of data reconciliation are reviewed and current problems are highlighted. In addition to defining the basic problem, we discuss the detection of gross errors in data and of pre-adjustment of data, finding departures from steady state, estimation of the variance structure of the data, observability of unmeasured quantities and redundancy of measurements.