I have a big question regarding the management of the defective rate(SPC management for attribute data). For variable data, I know we can use X-bar R Chart to do the SPC management. However when it comes to attribute data, it has become tricky. In my original plan I was going to use P chart to do the SPC management. The question is when using p char algorithm (UCL = p-bar + 3* sqtr((1-p-bar)*p-bar/n)) to calculate the UCL, the UCL is so small, almost 10 out of 35 of the points(defective rates) will be above the UCL. It indicates not only the whole process is not statistically stable, but also it is hopeless to do the P chart management. How can I do it with so many anomalies?! Before I was trying to use P chart to manage the defective rate, normally the algorithm for us to caculate the UCL for defective rate is that UCL = average defective rate + 3 * standard deviation of all defective rates. This UCL is large enough that there are not too many anomalies for us to check. The management on this UCL is doable. I know the algorithm of this UCL lacks the correct statistics support, however it can be implemented. Please help me on this problem, thank you.