SPC WITH CORRELATED OBSERVATIONS FOR THE CHEMICAL AND PROCESS INDUSTRIES

In the use of statistical control charts, violating the basic assumpti on of independent or uncorrelated data results in a chart that exhibit s poor statistical performance, resulting in an increased number of fa lse alarms. Autocorrelated data requires modifications to traditional control chart techniques. A method based on the exponentially weighted moving average that uses variable control limits is presented. Using simulation, we explore the shift detection properties of this moving c entre-line technique and will show how the detection capability of the procedure can be enhanced using supplemental tracking signal tests. G uidelines and conditions for use are also presented.