Use statistical process control when you want to make sure that the solution you created is maintained over time. By using these tools, your process can remain in control.
Stability of Process
Predictable process vs unpredictable.
Predictable: variation coming from common cause variation – or variation inherent to the environment of the process.
Unpredictable: special cause variation exists.
Specification Limits: Voice of the Customer. Shows what they will accept – or won’t/
Statistical Process Control Examples
Additional SPC Resources
- Great decision matrix here: https://www.moresteam.com/toolbox/statistical-process-control-spc.cfm
ASQ Six Sigma Green Belt SPC Questions
Statistical process control (SPC) is best defined as the use of
(A) Pareto charts to understand and control a process
(B) inputs to control critical and complex processes
(C) statistical methods to identify and remove manufacturing errors
(D) statistical methods to understand and control a process
Answer: (D) Statistical process control (SPC) is the practice of using statistical methods to understand and control a process.
Pareto charts may help you understand a process, but that is only one tool in a much larger suite that can be applied.
Using inputs to control critical and complex processes sounds a bit like guesswork. Yes, causal theory states that you can control an process by modulating its inputs but there’s little statistical effort in that. And studying the inputs to a process as you would in a SIPOC is very beneficial to understanding your process. But simply changing inputs may not make a process go under control. Perhaps the process as is currently designed will not work and needs to be redesigned.
Finally, SPC can be used for many types of processes, not only manufacturing. So we can discard choice C.