CORRECT steps for implementing SPC charts

You might have had some SPC training in the past, but it probably skipped over the correct steps to implement charting on the shop floor. Check it out, here they are:

1. Develop the total variance equation from the fishbone diagram of process variables. (Yes! This is the very first step!)

2. Determine which variance factors are adjustable, which are noise, and which can be set as a constant (CNX analysis.)
3. Choose the most important adjustable variable to chart (noise and constant variables can only generate "report card charts" which are of minimal value)
4. Ensure you have correct gaging and measurement techniques. Gage should have an ndc>10. For dimensionals, measure the same location on every part. Gage and measurement error tend to mask the true process variation with false normal distributions.

5. Minimize the variation of each of the participating variables - get the process in a steady state and capable. This includes eliminating your "special causes".
6. Prepare data in a time-ordered sequence as a capability study.

7. Accurately determine the correct distribution of the output. Distributions fitting software (e.g. Distribution Analyzer from variation.com are handy). NEVER ASSUME NORMALITY. NEVER ASSUME THE OUTPUT MUST BE NORMAL. Make sure they make sense! Determine if it is random or non-random (e.g. time function) data. Shewhart charts do not work with non-random variation.

8. Pick the correct chart to evaluate that variance factor (variable, attribute, Shewhart, non-Shewhart, etc.)
Please, please, please do NOT rubber stamp X-bar-R charts on the shop floor. Do your homework to get best results and not frustrate operators with nonsense.