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Data requirements for capability analysis

What are the data requirements for a capability analysis?

You can use individual observations or data in subgroups. You should verify that your process meets the following basic requirements for distribution fit and process stability:

Distribution fit
Your data must follow the assumed distribution for the analysis, such as a normal distribution (or nonnormal data transformed to fit a normal distribution) for Capability Analysis–Normal. The validity of the capability indices critically depends on the validity of the fit of the distribution used for the analysis. If your data do not follow the assumed distribution, the results will be inaccurate. If you are unsure which distribution best fits your data, use Individual Distribution Identification to identify an appropriate distribution or transformation.
Process stability
Your process must be stable and in control. A process is stable if it contains only variation from common causes, but no variation due to special causes.

Tools for determining whether a process meets the requirements for capability analysis

You can use the following tools in Minitab to assess whether your process satisfies the requirements for the analysis:

  • Xbar or Individuals charts to determine whether the process is in control. If the process is out of control, the capability indices are invalid.
  • R, S, or MR chart to track the variation in the data and assesses whether the process variation is acceptable.
  • A run chart to look for evidence of patterns in your data.
  • Probability plot to verify that a chosen distribution fits your data.
  • Capability histogram and capability plot to visually compare the distribution of data from your process to the specification spread. It also includes capability statistics to assess capability of your process quantitatively.

You can use Minitab’s Capability Sixpack to evaluate the main requirements for capability analysis. This analysis includes control charts, a histogram, a probability plot, and a capability plot, as well as major capability indices. Choose Stat > Quality Tools > Capability Sixpack and select the normal, nonnormal, or between/within analysis.

Example of using Capability Sixpack to check assumptions

Your company weaves rope that is 10 mm in width. You want to study the capability of the weaving process, so you collect twenty subgroups of rope, each containing five pieces, and use the Capability Sixpack to analyze the data. The probability plot indicates that the assumption of population normality is reasonable. The R chart and a Cp index greater than the reference value of 1.33 suggest stability of subgroup variation and indicate that the within-subgroup variation of your process is acceptable. However, the Pp index is less than the reference value of 1.33, so the overall capability of this process is inadequate due to variation between subgroups. The Xbar Chart and plot of the last 20 subgroups also depict this variation. This process needs improvement.

Source: Minitab Support files.

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