Process outputs are guaranteed to change over time, and Statistical Process Control (SPC) helps us separate statistically significant process changes from those changes that fall into the “normal process variation” category. SPC charts can also provide clues as to why significant process changes occur by isolating time periods and data points that show unusual behavior.
SPC goes beyond production monitoring. Here is a Range Control Chart (also known as an R Chart) used to in a gage study. The control limits on this chart (which were easily calculated from the data) provide us with some statistical guidance in knowing where a special-cause error might have affected our results. In this case, we see that something unusual likely happened when Appraiser A measured Part #9.
Control charts and accompanying guidelines exist for all data types, and the more common charts are –
- X̄ & R (average and range) charts for for continuous data measured in subgroups
- I-MR (individual and moving range) charts for individual data points (also continuous data)
- P-Charts for percent defective (attribute data)
- np Charts for defective counts (count data)