## Z 1.4 Inspection Levels

Question

I am using a reduced switching rule and I don’t understand the meaning of the numbers in the first box. Total noncomforming less than limit number? What’s my limit number?Does production stability mean capability? Would I use 1.33?  The table has an arrow to reduced, so would I move to the next box?

The ANSI/ASQ Z1.4 standard has three inspection levels: normal, reduced and tightened inspection.  Initially you start at normal inspection, and can move to either tightened or reduced inspection depending on how lots are dispositioned.  Based on Figure 1 of the standard, the determination to move amongst the levels can be ascertained.  When you get to the reduced inspection level (Table II-C), you need to read the footnote (†).  It states “If the acceptance number has been exceeded, but the rejection number has not been reached, accept the lot, but reinstate normal inspection.”

A stable process or production is less about a capability index, and more about the control chart of the data showing a stable process.  In other words, the process is stable over time.

Steven Walfish

## Z1.4:2008, Using Acceptance Quality Limit (AQL)

Q: I have a question about how to use ANSI/ASQ Z1.4-2008 Sampling Procedures and Tables for Inspection by Attributes.

I am looking to achieve a 99.5% production yield.  How do I calculate that using the Acceptance Quality Limit (AQL) in this standard?  Is it as simple as taking (100-AQL) to calculate the expected yield?

A: The ANSI Z1.4-2008 standard is not intended for calculating production yield or expected production yield.  The AQL is the maximum percent non-conforming that can be considered acceptable as a process average.  Typically we set this as the percent defective that would be accepted at a 95% confidence.  If you want to sample such that you have 95% confidence that the average production yield is 99.5%, you can find a sampling plan with an AQL of 0.5%.  Also, please understand that the tables in the standard are not exact value for AQL.  Using the binomial distribution (or hypergeometric for sampling with no replacement) you can calculate the exact probability.

Steven Walfish
Secretary, U.S. TAG to ISO/TC 69
ASQ CQE
Statistician, GE Healthcare
http://statisticaloutsourcingservices.com/

For more on this topic, please visit ASQ’s website.