Hello guys,
For Attribute GRR according to AIAG 4th edition, they mention the sample size determination as follows (pages 140, 141):
// Sample Size:
The question always arises: “How many samples should be used in the study?” To the dismay of most people, the answer is “enough”. The purpose
of any measurement study (variables or attribute) is to understand the properties of the measurement system.. A sufficient number of samples should be selected to cover the expected operating range (see also Chapter II Section C). With attribute measurement systems, the area of interest are the Type II areas (see Chapter I, Section B). If the inherent process capability is good (i.e., large Cp, Cpk or Pp, Ppk) then a small random sample may not have many (or any) samples in this area. This means that as the process capability improves , the required random sample for the attribute study should become larger).
In the example above, the indices were Pp, Ppk = 0.5 (i.e. an expected process performance of approximately 13% nonconformance), the sample selected was 50.
An alternate approach to large samples is a “salted sample” where parts are selected specifically from the Type II areas to augment a random sample to ensure that the effect of appraiser variability is seen. //
Can anyone explain the way they calculate 50 samples from ppk =0.5?
And in the alternate approach, what is "salted sample", how they select sample size with this?
Thank you guys in advance for your great help.
For Attribute GRR according to AIAG 4th edition, they mention the sample size determination as follows (pages 140, 141):
// Sample Size:
The question always arises: “How many samples should be used in the study?” To the dismay of most people, the answer is “enough”. The purpose
of any measurement study (variables or attribute) is to understand the properties of the measurement system.. A sufficient number of samples should be selected to cover the expected operating range (see also Chapter II Section C). With attribute measurement systems, the area of interest are the Type II areas (see Chapter I, Section B). If the inherent process capability is good (i.e., large Cp, Cpk or Pp, Ppk) then a small random sample may not have many (or any) samples in this area. This means that as the process capability improves , the required random sample for the attribute study should become larger).
In the example above, the indices were Pp, Ppk = 0.5 (i.e. an expected process performance of approximately 13% nonconformance), the sample selected was 50.
An alternate approach to large samples is a “salted sample” where parts are selected specifically from the Type II areas to augment a random sample to ensure that the effect of appraiser variability is seen. //
Can anyone explain the way they calculate 50 samples from ppk =0.5?
And in the alternate approach, what is "salted sample", how they select sample size with this?
Thank you guys in advance for your great help.