To ensure that your results are valid, consider the following guidelines when you collect
data, perform the analysis, and interpret your results.
- The data should be continuous
-
Continuous data are measurements that may potentially take on any numeric
value within a range of values along a continuous scale, including
fractional or decimal values. Common examples include measurements such as
length, weight, and temperature.
If you have attribute data, such as counts of defectives or defects, use
Binomial Capability
Analysis or Poisson Capability
Analysis.
- Collect enough data to obtain reliable estimates of process capability
- Try to collect at least 100 total data points. If you do not collect a
sufficient amount of data over a long enough period of time, the data may not
accurately represent different sources of process variation and the estimates
may not indicate the true capability of your process.
- The process must be stable and in control
- If the current process is not stable, then the capability indices cannot be
reliably used to assess the future, ongoing capability of the process. If you
are unsure whether your process is in control, use a control chart to evaluate
process stability before you perform this analysis.