Should individuals control chart in XmR have control limits adjusted?

QUESTION: I have over 1,000 data points where data does not appear to be normally distributed. Should I make some sort of adjustment to the upper control limit (UCL) and lower control limit (LCL) for this individuals control chart (XmR) case so that the traditional probability of finding outliers is retained?

RESPONSE: To answer your question you should not adjust the control limits; however, that should only be part of the consideration. I noted that you made no mention of process capability in your question or subgrouping interval considersations. These are important issues that need to be addressed.

Remember out of control signals are only to identify special cause occurrence but what if common cause variability is unsatisfactory relative to customer needs? Control charts of continuous data do not address this point. When common cause variability has, for example, too high non-conformance, this occurances requires different action; i.e., you need to undertake a general process improvement project where all the data in the latest region of stability can give you insight to what should be done differently to improve.

I highly suggest that you keep an open mind when reading the Quality Digest article below and its links. This is one of the later articles where Donald Wheeler and I described our differing points of view and my inclusion of process capability statements within this analysis discussion, noting that this article was referenced earlier in another comment.

Referenced article: “NOT Transforming the Data Can Be Fatal to Your Analysis: A case study, with real data, describes the need for data transformation.”