SOME OMNIBUS EXPONENTIALLY WEIGHTED MOVING AVERAGE STATISTICAL PROCESS MONITORING SCHEMES

Exponentially weighted moving average (EWMA) quality-monitoring schemes capable of detecting changes in both location and spread, referred to as omnibus EWMA's, are proposed. Omnibus EWMA's are based on the exponentiation of the absolute value of the standardized sample mean of the observations. The process target mean and standard deviation are used for standardizing. Design procedures and considerations, including a fast initial response feature, are discussed. Average run lengths for exponents of .5 and 2 and various values of the weighting constant are presented. The proposed schemes are compared with each other and with a number of selected, well-known omnibus schemes and a proposed omnibus cumulative sum scheme. Schemes with different sample sizes are used, and off-target models include both static and dynamic alternatives. Comparisons are based on average number of observations to detection and expected loss due to poor quality. One of the omnibus EWMA schemes is shown to be best with regard to expected loss if a uniform prior is placed on the off-target models studied.