Estimating measurement uncertainty: reconciliation using a cause and effect approach

A strategy is presented for applying existing data and planning necessary additional experiments for uncertainty estimation. The strategy has two stages: identifying and structuring the input effects, followed by an explicit reconciliation stage to assess the degree to which information available meets the requirement and thus identify factors requiring further Study. A graphical approach to identifying and structuring the in put effects on a measurement result is presented. The methodology promotes consistent identification of important effects, and permits effective application of prior data with minimal risk of duplication or omission. The results of applying the methodology are discussed, with particular reference to the use of planned recovery and precision studies.