Z1.4 and Z1.9 in micro testing and API chemical analysis


Q: I work at a cosmetics manufacturing company that produces sunscreen in bulk amounts. When we make 3,000 kg of sunscreen, we will use that in 10,000 units of final sunscreen products which will weigh 300 g each.

How many samples do I need to collect from the 10,000 units to pass the qualification?

The products need to pass both attribute and variable sampling tests such as container damage, coding error, micro testing, and Active Pharmaceutical Ingredients (API)  failure. Almost 100 percent of final products were inspected for appearance error, but a small number of them should be measured for micro testing and API chemical analysis.

For Z1.4-2008: Sampling Procedures and Tables for Inspection by Attributes, we have to collect a sample of 200 (lot size of 3,201-10,000; general inspection level II;  acceptable quality level 4.0 L), and more than 179 should pass for qualification.

For Z1.9-2008: Sampling Procedures and Tables for Inspection by Variables for Percent Nonconforming, we have to collect a sample of 25 (lot size of 3,201-10,000; general inspection level II; acceptable quality level 4.0, L), to meet the requirement of 1.12 percent of nonconformance.

Which sampling plan should we follow for micro testing and API chemical analysis?

A: If the micro test is pass/fail, then you should use Z1.4. The API chemical test  probably yields a numerical result for which you can calculate the average and standard deviation. Then, the proper standard to use is Z1.9. If the micro test gives you a numerical result, then you can use Z1.9 for it as well.

One thing to consider is the fact that the materials are from a
batch. If the batch can be assumed to be completely mixed without settling or separation prior to loading into final packaging, then the API chemical test may only need to be done on the batch, not on the final product. Micro testing, which can be affected by the cleanliness of the packaging equipment, probably needs to be done on the final product.

Brenda Bishop
U.S. Liaison to TC 69/WG3
ASQ CQE, CQA, CMQ/OE, CRE, SSBB, CQIA
Belleville, Illinois

Related Resources:

Getting the Right Data Up Front: A Key Challenge, Quality Engineering, open access

Rational decisions require transforming data into useful information by appropriate analyses. Such analyses, however, can be only as good as the data upon which they are based. In this article, the authors urge that careful consideration be given, up front, to procuring the right data and provide some guidelines. Read more.

A Graphical Tool for Detection of Outliers in Completely Randomized, Unreplicated 2k and 2k-P Factorials, Quality Engineering, open access

With the increased awareness of statistical methods in industry today, many non-statisticians are implementing statistical studies and conducting statistically designed experiments (DOEs). With this increased use of DOEs by non-statisticians in applied settings, there is a need for more graphical methodologies to support both analysis and interpretations of DOE results. Read more.

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One Response to Z1.4 and Z1.9 in micro testing and API chemical analysis

  1. For Micro testing is not suitable to use the above mentioned standards due to variability in micro testing.
    Currently, for micro testing three groups of samples are taken. Each group should be sampled at the same time (three bottiles for example) that’s to say 9 bottles in the whole lot.
    The difference between the micro properties of the products defines the kind of sampling:
    1) If the product is aqueous it is recommended to test first and the last bottles and only test the third group on a random basis.
    2) If the product is not aqueous or it was proved to inhibit microorganisms growth you can test the initial bottles and take the two other samples in a random manner.
    Have you a nice weekend.
    Néstor Aversa
    CQE – Biochemist

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