Cpk calculator. Capability you can see.
Cpk, the process capability index, shows how comfortably a process fits inside its tolerance: it is the distance from the mean to the nearest specification limit divided by three standard deviations. Measure example shafts one by one or thirty at a time and this simulator builds the histogram and calculates the mean, standard deviation, Cp, Cpk and the expected share of parts out of tolerance.
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Three steps. One clear answer.
- 01
Measure the next part, or thirty at once, on a shaft specified at 25.00 ± 0.05 mm.
- 02
Watch the histogram build and read the mean, standard deviation and Cpk once ten or more parts are measured.
- 03
Apply the corrective action to see how re-centring and a tighter spread lift Cpk above 1.33.
Cp = (USL − LSL) ÷ 6σ and Cpk = min(USL − μ, μ − LSL) ÷ 3σ, where μ is the mean of the measured parts and σ their sample standard deviation (n − 1). The expected share out of tolerance assumes a normal distribution. A Cpk of 1.33 is the common minimum for an established process and 1.67 for new or critical characteristics. Strictly, a figure calculated from the overall standard deviation of all parts is Ppk; Cpk uses the within-subgroup variation from a control chart. For a stable process the two are close. Measurements are simulated for an example part.
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[email protected]What is a good Cpk value?
1.33 or higher is the common minimum for an established process, which means the nearest limit is four standard deviations from the mean. Many buyers ask for 1.67 on new or safety-critical characteristics.
What is the difference between Cp and Cpk?
Cp compares the tolerance width with the process spread and ignores where the process is centred. Cpk also accounts for centring, so it is always equal to or lower than Cp.
How many parts do I need to calculate Cpk?
At least 30 is a common minimum, and 50 to 125 measurements in subgroups gives a more reliable figure. With fewer than 10 the result moves a lot from part to part.
What is the difference between Cpk and Ppk?
Cpk uses short-term, within-subgroup variation and shows what the process can do. Ppk uses the overall variation of all parts and shows what it actually delivered. For a stable process they are close.
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