Better Risk-Management Alternatives to AQL Sampling Plans in Incoming QC Inspection

Instructor: John N Zorich
Product ID: 706022
Training Level: Intermediate
  • Duration: 90 Min
Attend this webinar to learn the serious disadvantages of basing incoming QC inspection on AQL sampling plans (e.g., ANSI Z1.4 or Squeglia's C=0). You will also learn several better risk management alternatives that provide much better quality control and risk management.
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Why Should You Attend:

The pros and cons of the 2 most widely used sampling plans (ANSI Z1.4, and Squeglia's C=0) are examined in detail, focusing especially on the weaknesses of such plans in regards to meeting regulatory requirements. The advantages of "confidence/reliability" calculations are explained. Such calculations are demonstrated for Attribute data (pass/fail, yes/no data) as well as for variables data (i.e., measurements). If variables data is "Normally distributed" the calculations are extremely simple. The webinar explains how to handle "non-Normal" data, and provides the methods, formulas, and tools to handle non-normality.

The training includes a discussion of how one OEM manufacturer has implemented "confidence/reliability" calculations instead of AQL sampling plans for all of its clients. And suggestions are given for how to use "confidence/reliability" QC specifications instead of "AQL" QC specifications. The use of "reliability plotting" for assessing product reliability during R&D is also discussed.

The training also includes an examination of ISO and FDA regulations and guidelines regarding the use of statistics, especially in regards to Sampling Plans.

Areas Covered in the Webinar:

  • AQL and LQL sampling plans
  • OC Curves
  • AOQL
  • ANSI Z1.4
  • Squeglia's C=0
  • Confidence/Reliability calculations for
    • attribute data
    • Normally-distributed variables data
    • non-Normal data
  • Transformations to Normality
  • K-tables
  • Normal Probability Plot
  • Reliability Plotting

Who Will Benefit:

  • QA/QC Supervisor
  • Process Engineer
  • Manufacturing Engineer
  • QC/QC Technician
  • Manufacturing Technician
  • R&D Engineer
Instructor Profile:
John N Zorich

John N Zorich
Statistical Consultant and Trainer, Statistical Consultant

John Zorich has spent almost 40 years in the medical device manufacturing industry; the first 20 years were as a "regular" employee in the areas of R&D, Manufacturing, QA/QC, and Regulatory; the next 15 years were as a consultant in the areas of QA/QC and Statistics. These last few years were as a trainer and consultant in the area of Applied Statistics only. His consulting clients in the area of statistics have included numerous start-ups as well as large corporations such as Boston Scientific, Novellus, and Siemens Medical. His experience as an instructor in applied statistics includes having given annual 3-day seminars for many years at Ohlone College (San Jose CA), and previously having given that same course for several years for Silicon Valley ASQ Biomedical. He's given numerous statistical seminars at ASQ meetings and conferences. And he creates and sells validated statistical software programs that have been purchased by more than 110 companies, world-wide.

Topic Background:

Almost all manufacturing companies spend time and money to inspect purchased parts upon receipt, in order to evaluate part quality before the parts Supplier is paid. "AQL" sampling plans are used almost universally for such inspections. However, AQL plans actually provide very little information about part quality.

A better way to assess the quality of purchased parts is to use "confidence/reliability" calculations. Such calculations are very easy to perform using tables and/or an electronic spreadsheet.

ISO 9001 and ISO 13485 requirements include establishing "processes needed to demonstrate [product] conformity"; FDA's GMP (21CFR820) requires that "sampling methods are adequate for their use". An AQL sampling plan does not provide what is needed to meet either of those requirements. FDA guidelines state that "A manufacturer shall be prepared to demonstrate the statistical rationale for any sampling plan used" --- it is not possible to "demonstrate" that an AQL sampling plan ensures product quality.

On the other hand, confidence/reliability calculations can be easily shown to provide evidence of product quality, and the statistical rationale for such calculations is easy to explain and demonstrate.

Follow us :
FDA's Medical Device Software Regulation Strategy
Managing Your Complaints and Obstacles in Post-Market Requirements

Refund Policy

Registrants may cancel up to two working days prior to the course start date and will receive a letter of credit to be used towards a future course up to one year from date of issuance. ComplianceOnline would process/provide refund if the Live Webinar has been cancelled. The attendee could choose between the recorded version of the webinar or refund for any cancelled webinar. Refunds will not be given to participants who do not show up for the webinar. On-Demand Recordings can be requested in exchange.

Webinar may be cancelled due to lack of enrolment or unavoidable factors. Registrants will be notified 24hours in advance if a cancellation occurs. Substitutions can happen any time.

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