Simple adjustments to improve control limits on attribute charts

Many SPC software packages determine control chart limits for attribute data using normal approximations. For some sample sizes and/or process parameter values these approximations are far from adequate, mainly due to skewness in the exact distribution. Significant improvements can be made to the probabilistic accuracy of control limits by simple adjustments derived from Cornish and Fisher expansions for percentage points. The adjustments are preferable to normalizing transformations in that the original scale of the data is retained and most SPC packages allow self-determined control limits to be inserted. The overall objective is to bring operational meaning and practice for attribute charts more into line with charts for variables.