the process is centered on the . Cpk is more widely used than Cp, since it takes into account the mean and the standard deviation in its calculation. Most capability indices estimates are valid only if the sample size used … Pp, Ppk vs Cp, CPK. Cp will normally be used in conjunction with the Cpk measure, so that both centering and spread can be understood. Use Pp & Ppk when you are initially setting up your process. When these assumptions are not met the values are not valid. If both Cp and Cpk are greater than or equal to 1 then the process is considered capable. Pp, Ppk are more liberal where Cp, CPK are more conservative. Cpk considers the mean of the process and calculates two values ([Cp-usl = (USL -)/3] and [Cp-lsl = (- LSL)/3]). specification range • Cp=Cpk when process is centered. If your process is not stable, the results will be meaningless. July 2014 This month’s publication takes a look at process capability calculations and the impact non-normal data has on the results. A perfectly centered process where the mean is the same as the midpoint will have a "k" value of 0. Most capability indices estimates are valid only if the sample size used is "large enough". This prediction enables us to “qualify" a new manufacturing process as being fit for use in production. The addition of "k" in Cpk quantifies the amount of which a distribution is centered, in other words it accounts for shifting. Caution: Only after a process is under statistical control, can one safely assume that the mean and standard deviation to have a stable values over time. Large enough is generally thought to be about 50 independent data values. There are three key assumptions for Cp or Cpk 1. A perfectly centered process will have Cp = Cpk. Cp considers only the spread and not the centering of the process. the process being analyzed should be under statistical control. Cp gives the process owner an idea of potential but doesn’t imply anything about what’s actually IN THE PROCESS which is why we need to look at Cpk also and graphical representations. If Cp = Cpk, the process is centered at the midpoint of the specifications. Cpk 3.0 Relationship between Process . Also, the statement of why to use Cpk is because we can only get damaged on the closest side implies you can’t get defects on the other side. if Cp>Cpk, then the process is off-center. Large sample size 3. The index Cp provides a measure of potential process capability i.e. Use Cp & Cpk once the process is in a state of statistical control. Cp & Cpk use an estimate for the standard deviation using the R Bar / d2 method. Cpk value can be found if we know the Cp and can calculate the k value also i.e. Stable process 2. Related reading: What is Capability Analysis? The most common method of expressing process capability involves calculating a Cpk value, i.e., a process has a Cpk = 1.54. The Cpk is an indicator of how centered your process is (use Cp and Cpk together to evaluate this). Cpk uses "s-short-term" to predict the behavior of the process. Cpk on the other hand helps indicate how centered the data is within the range. In actual practice, this shouldn’t happen very often. Where the Cp and Cpk values are equal, then the process is centered between the specifications, where not equal, then the greater the gap between the two values, the greater the shift in the process mean from the nominal mean. Cpk = Cp(1-k), where K can be any value from 0 to 1. The Cp & Cpk calculation is based on the process mean & range and has nothing to do with how many points are in or out of spec. Cpk or Ppk is less than CP or Pp. The minimum value of "k" is 0 and the maximum is 1.0. The Cpk calculation assumes that the data is normally distributed. Consequently, you can have a capable process (Cp > 1) and not be making any good product. Normal distribution. 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