Hi Candi,
Here is what I use when performing process qualifications. Sorry for the copy/paste. Hope is is readable. Shoot me an email if you need some clarification.
Best,
Scott
Sample size determination for process qualification and validations.
Confidence level and reliability % will be chosen based on risk analysis.
The following confidence and reliability levels should be used corresponding to the severity ranking from the risk document.
*Not many on the forum will agree with the C/R table below; too low or too high. The table that I am sharing is from a specific project at a former employer (medical device).
Severity (Confidence/Reliability)
CA 95/95
CR 90/95
M 90/90
N 80/90
Sample size for attribute data
Required Sample Size
Confidence Level
Reliability 80% 90% 95% 99% 99.9%
80% 8 11 13 21 31
85% 10 14 18 28 42
90% 16 22 28 44 66
95% 31 45 58 90 135
99% 160 229 298 458 687
Juran, J.M., and Godfrey, A.B., Juran?s Quality Handbook, McGraw-Hill, Inc.
Sample size for variable data when nothing is known about the process or its distribution
Required Sample Size
Confidence Level
Reliability 50% 70% 90% 95% 99% 99.5%
80% 9 12 18 22 31 34
85% 11 16 25 30 42 47
90% 17 24 38 46 64 72
95% 34 49 77 93 130 146
99% 168 244 388 473 662 740
Table X of Appendix II, Juran, J.M., and Godfrey, A.B., Juran?s Quality Handbook, McGraw-Hill, Inc.
Sample size for variable data when process average, specification limits, and process standard deviation are all known.
Use the one or two sided factors depending on whether the specification is one or two sided. The ?K? values in the table are determined from the following:
Minimum of (average ? LSL)/s, (USL ? average)/s
Where ?s? is the standard deviation and LSL and USL are the lower and upper specification limits.
When the ?K? value falls between 2 values of ?n?, round to the larger sample size.