Actions Panel
90 Min Virtual Webinar Smarter, Not Harder: More Effective Alternatives to AQL Sampling Plans in QC Inspection Risk Management
By Compliance SpotlightFollow
Date and time
Monday, September 25 · 12 – 1pm PDT
Location
Online
Refund Policy
Contact the organizer to request a refund.
About this event
- 1 hour
- Mobile eTicket
Description:
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.
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 regard 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 regard 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
Report this event
