Sampling by Variables: ANSI/ASQ Z1.9 -By AtoZ Compliance

Key Take Away :

This webinar will enable you to understand how to use ANSI code/ASQ Z1.9 (formerly MIL-STD 414) for acceptance sampling by variables, or continuous-scale dataand, how to use switching rules for normal, tightened, and reduced inspection.

Overview :

ANSI/ASQ Z1.9 (formerly MIL-STD 414) is a generally accepted sampling plan that uses continuous-scale sample statistics—usually the sample average and either the sample standard deviation or a known process standard deviation—to determine whether a production lot should be accepted or rejected.

The ANSI compliant sampling plan depends on the prescribed level of inspection, the acceptable quality level (AQL), the lot size, and whether inspection is normal, tightened, or reduced. The latter status depends on past performance.

Rejected lots will result in tightened inspection, while a series of accepted lots under steady production conditions may allow reduced inspection.

Why Should You Attend :

Customers, whether internal or external, may require use of ANSI guidelines/ASQ Z1.9 to determine whether production lots should be accepted or rejected. It is therefore important to know how to use the standard correctly.

This includes not only determination of the correct sampling plan based on lot size, quality criteria, and inspection status, but also use of the switching rules for normal, tightened, and reduced inspection.

It is emphatically vital to recognize that ANSI regulations/ASQ Z1.9 relies on the assumption that the critical to quality (CTQ) characteristic follows the normal or bell curve distribution. If this assumption is not met, the standard’s sampling plans will not work correctly.

Areas Covered In This Webinar :

Sampling by variables is far more efficient than sampling by attributes (pass/fail) data as described in ANSI standards/ASQ Z1.4 (formerly MIL-STD 105). Far fewer items must be inspected, although it is necessary to obtain a real number measurement as opposed to a pass/fail result
It is vital to recognize that ANSI/ASQ Z1.9 relies on the assumption of normally distributed data, and it is therefore necessary to perform tests for normality before using these food safety test sampling plans
The sampling plan, in terms of the required sample size n and the acceptance criterion, depends on (1) the lot size, (2) the inspection level, (3) the prescribed acceptable quality level (AQL), and whether inspection is normal, tightened, or reduced. The plan will also depend on whether the standard deviation is known, or must be estimated from the sample statistics; smaller samples are generally required in the former case because the only uncertainty is as to the lot’s mean (as estimated from the sample average)
The next step is to calculate the acceptability criterion (standard deviations between the specification and the specification limit), also known as the quality index. It is then possible to estimate the lot’s nonconforming fraction, and compare this against tabulated values to determine whether the lot should be accepted or rejected
The sample range also can be used to estimate the lot’s standard distribution, although not much time will be spent on this. The sample standard deviation contains somewhat more information, and is easy to calculate on modern calculators and computers
The webinar handout includes an appendix with information on how the operating characteristic curves and estimated nonconforming fractions are obtained. This information is not provided in the standard itself.
This webinar also includes an appendix on, to paraphrase Otto von Bismarck, “how laws and sausages are made.” That is, it shows how elements of the operating characteristic curves (probability of acceptance versus quality of the lot) and estimated nonconforming fraction are calculated.

This information is not included in the standard, and it is not required for use of the standard. An Excel spreadsheet is also provided with tables B5 and D5 of the standard (as calculated independently and checked against the standard). These are estimates of the nonconforming fraction for situations in which the sample standard deviation and process standard deviation respectively are used.

This webinar uses tables from MIL-STD 414 (public domain government publication) and not ANSI/ASQ Z1.9 (copyrighted) to show how to use the standard. The sample codes differ between the standards, but the actual procedure for using them is essentially identical.

Learning Objectives :

Know how to use the lot size, inspection level, AQL, and inspection status to select the correct sampling plan
Know how to perform the necessary OSHA compliance calculations to determine whether the lot is acceptable, and to estimate its nonconforming fraction
Know the difference between Form 1 plans in which the sample’s calculated acceptance criterion is compared to a tabulated value, and Form 2 plans in which estimated nonconforming fractions are compared to tabulated values
Know how to use the plan when the lot standard deviation is known in advance, as it might be from the history of a controlled process, and when only the sample standard deviation is available
Know how to use the standard’s switching rules for normal, tightened, and reduced inspection

Who Will Benefit :

Quality Engineers
Quality Technicians
Quality Inspectors
For more information, please visit : https://www.atozcompliance.com/trainings-webinar/cross-industry-functions/quality-management-system/ansi-compliant-code-guidelines/william-a-levinson/300229?utm_source=refpdf&utm_medium=23Feb
Email: support@atozcompliance.com
Toll Free: +1- 844-414-1400
Tel: +1-516-900-5509

Level:
Intermediate

Speakers Profile :

William A. Levinson
William A. Levinson, P.E., is the principal of Levinson Productivity Systems, P.C. He is an ASQ Fellow, Certified Quality Engineer, Quality Auditor, Quality Manager, Reliability Engineer, and Six Sigma Black Belt.

He is also the author of several books on quality, productivity, and management, of which the most recent is The Expanded and Annotated My Life and Work: Henry Ford’s Universal Code for World-Class Success.

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