Updated 2022-06-18
Statistical Process Control (SPC) uses elementary statistical analysis to determine when an event happened. This gives process managers permission to investigate and possibly make a change. The process could be a manufacturing process, or a chemical process, or a political process, or an environmental process. The term process means that some outcome of interest, which is being observed, is affected by natural and controlled influences. Processes are subject to random perturbations, so even if there is no real change, the observation of the outcome continually fluctuates. It is noisy. We only want take corrective action if there is real change, not in response to noise. SPC tempers management action, saves effort and cost, and actually reduces variability (improving quality). Its major acceptance in manufacturing originated in the 1940s, and now SPC concepts have evolved to be represented by 6-sigma practices.
You can download a pdf introduction to SPC here. It is is an excerpt from Chapter 21 in Rhinehart and Bethea, Applied Engineering Statistics, 2nd Edition, CRC Press, Boca Raton, FL, 2022, ISBN: 9781032119489. r3eda-SPC-2021-08-30.pdf
You can download an Excel/VBA simulator to watch SPC sampling and X-Bar and R Chart actions here. SPC-Demonstration-2022-06-18.xlsm