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ASTM F3263-17(2025)

Standard Guide for Packaging Test Method Validation
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1.1Ā This guide provides information to clarify the process of validating packaging test methods specific for an organization utilizing them as well as through inter-laboratory studies (ILS), addressing consensus standards with inter-laboratory studies (ILS) and methods specific to an organization.

1.1.1Ā ILS discussion will focus on writing and interpretation of test method precision statements and on alternative approaches to analyzing and stating the results.

1.2Ā This document provides guidance for defining and developing validations for both variable and attribute data applications.

1.3Ā This guide provides limited statistical guidance; however, this document does not purport to give concrete sample sizes for all packaging types and test methods. Emphasis is on statistical techniques effectively contained in reference documents already developed by ASTM and other organizations.

1.4Ā This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.

1.5Ā This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

4.1Ā Addressing consensus standards with inter-laboratory studies (ILS) and methods specific to an organization. Test methods need to be validated in many cases, in order to be able to rely on the results. This has to be done at the organization performing the tests but is also performed in the development of standards in inter-laboratory studies (ILS), which are not substitutes for the validation work to be performed at the organization performing the test.

4.1.1 Validations at the Testing Organization— Validations at the test performing organization include planning, executing, and analyzing the studies. Planning should include description of the scope of the test method which includes the description of the test equipment as well as the measurement range of samples it will be used for, rationales for the choice of samples, the amount of samples as well as rationales for the choice of methodology.

4.1.2 Objective of ILS Studies— ILS studies (per E691-14) are not focused on the development of test methods but rather with gathering the information needed for a test method precision statement after the development stage has been successfully completed. The data obtained in the interlaboratory study may indicate however, that further effort is needed to improve the test method. Precision in this case is defined as the repeatability and reproducibility of a test method, commonly known as gage R&R. For interlaboratory studies, repeatability deals with the variation associated within one appraiser operating a single test system at one facility whereas reproducibility is concerned with variation between labs each with their own unique test system. It is important to understand that if an ILS is conducted in this manner, reproducibility between appraisers and test systems in the same lab are not assessed.

4.1.3 Overview of the ILS Process— Essentially the ILS process consists of planning, executing, and analyzing studies that are meant to assess the precision of a test method. The steps required to do this from an ASTM perspective are; create a task group, identify an ILS coordinator, create the experimental design, execute the testing, analyze the results, and document the resulting precision statement in the test method. For more detail on how to conduct an ILS refer to E691-14.

4.1.4 Writing Precision and Bias Statements— When writing Precision and Bias Statements for an ASTM standard, the minimum expectation is that the Standard Practice outlined in E177-14 will be followed. However, in some cases it may also be useful to present the information in a form that is more easily understood by the user of the standard. Examples can be found in 4.1.5 below.

4.1.5 Alternative Approaches to Analyzing and Stating Results—Variable Data:

  • 4.1.5.1 Capability Study:
    • (1)Ā A process capability greater than 2.00 indicates the total variability (part-to-part plus test method) of the test output should be very small relative to the tolerance. Mathematically,

      Equation F3263-17R25_1
    • (2)Ā Notice, σTotal in the above equation includes σPart and σTM. Therefore, two conclusions can be made:
      • (a)Ā The test method can discriminate at least 1/12 of the tolerance and hence the test method resolution is adequate Therefore, no additional analysis such as a Gage R&R Study is necessary.
      • (b)Ā The measurement is precise relative to the specification tolerance.
    • (3)Ā In addition, since the TMV capability study requires involvement of two or more operators utilizing one or more test systems, a high capability number will prove consistent test method performance across operators and test systems.
  • 4.1.5.2 Gage R&R Study:
    • (1)Ā The proposed acceptance criteria below for %SV, %R&R, and %P/T came from the industry-wide adopted requirements for measurement systems. According to Automotive Industry Action Group (AIAG) Measurement System Analysis Manual (4th edition, p. 78), a test method can be accepted if the test method variation (σTM) counts for less than 30 percent of the total variation of the study (σTotal).
    • (2)Ā This is equivalent to:A process capability greater than 2.00 indicates the total variability (part-to-part plus test method) of the test output should be very small relative to the tolerance. Mathematically,

      Equation F3263-17R25_2
    • (3)Ā When historical data is available to evaluate the variability of the process, we should also have:

      Equation F3263-17R25_3
    • (4)Ā For %P/T, another industry-wide accepted practice is to represent the population using the middle 99 % of the normal distribution.5 And ideally, the tolerance range of the output should be wider than this proportion. For a normally distributed population, this indicates:

      Equation F3263-17R25_4
    • (5)Ā The factor 5.15 in the above equation is the two-sided 99 % Z-score of a normal distribution. Therefore:

      Equation F3263-17R25_5
    • (6)Ā In practice this means that a test method with up to 6 % P/T reproducibility would be effective at assessing the P/T for a given design.
  • 4.1.5.3 Power and Sample Size Study:
    • (1)Ā When comparing the means of two or more populations using statistical tests, excessive test method variability may obscure the real difference (ā€œSignalā€) and decrease the power of the statistical test. As a result, a large sample size may be needed to maintain an adequate power (≄ 80 %) for the statistical test. When the sample size becomes too large to accept from a business perspective, one should improve the test method before running the comparative test. Therefore, an accept /reject decision on a comparative test method could be made based on its impact on the power and sample size of the comparative test (ex. 2 Sample T-test).

4.2 Attribute Test Method Validation:

4.2.1 Objective of Attribute Test Method Validation— Attribute test method validation (ATMV) demonstrates that the training and tools provided to inspectors enable them to distinguish between good and bad product with a high degree of success. There are two criteria that are used to measure whether an ATMV has met this objective. The primary criterion is to demonstrate that the maximum escape rate, β, is less than or equal to its prescribed threshold of βmax. The parameter β is also known as Type II error, which is the probability of wrongly accepting a non-conforming device. The secondary criterion is to demonstrate that the maximum false alarm rate, α, is less than or equal to its prescribed threshold of αmax. The parameter α is also known as Type I error, which is the probability of wrongly rejecting a conforming device.

4.2.2 Overview of the ATMV Process— This section describes how an ATMV typically works. In an attribute test method validation, a single, blind study is conducted that is comprised of both conforming and non-conforming units. The ATMV passes when the requirements of the both sampling plans are met. The first sampling plan demonstrates that the test method meets the requirements for the maximum allowable beta error (escape rate), and the second sampling plan demonstrates that the test method meets the requirements for the maximum allowable alpha error (false alarm rate). In other words, the test method is able to demonstrate that it accepts conforming units and rejects non-conforming units with high levels of effectiveness. The beta error sampling plan will consist entirely of nonconforming units. The total number of beta trials conducted by each inspector6 are pooled together, and their total number of misclassifications (nonconforming units that

SDO ASTM: ASTM International
Document Number F3263
Publication Date Oct. 1, 2025
Language en - English
Page Count 14
Revision Level 17(2025)
Supercedes
Committee F02.50
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