If you have worked with count charts with large denominators, you have probably seen control limits that seem too narrow to be of much value. The p-chart is one of the attributes charts with this flaw.
A p-chart counts two things: 1) the number of non-conforming items (the numerator) and 2) the number of items inspected (the denominator). If you look at the glass half-full rather than half-empty, you might count the number of conforming items (rather than non-conforming). In either case, when the denominator is large, a problem may be present.
Consider the following chart which shows a p-chart from a plastic shopping bag manufacturer.
This chart measures the percent of plastic bags that failed a particular test. The bag manufacturer averages about 20,000 bags inspected in each sample and about 600 failures. As you can tell by looking at this chart, the limits seem too tight to be useful. The control limits are considered to be overly-dispersed.
