Process Capability Analysis by means of Confidence Reliability Calculations

The webinar explains how to calculate confidence/reliability for data that is either pass/fail (i.e., "attribute" data), this begins with a discussion of relevant regulatory requirements, as motivation for calculating "confidence/reliability".

Michael Brodsky
Instructor:
Michael Brodsky
Date:
Monday, February 24, 2020
Time:
09:00 AM PST | 12:00 PM EST
Duration:
60 Minutes

More Trainings by this Expert   Product Id : 502911

Price Details
$150 Live
$290 Corporate Live
$190 Recorded
$390 Corporate Recorded
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Overview:

The webinar begins with a discussion of relevant regulatory requirements, as motivation for calculating "confidence/reliability". Then, some vocabulary and basic concepts are discussed.

Next, detailed descriptions are given for how to calculate confidence/reliability for data that is either pass/fail (i.e., "attribute" data), normally-distributed measurement data, non-normally distributed measurement data that can be transformed into normality, or non-normally distributed measurement data that cannot be transformed into normality. Spreadsheets are shown as examples of how to implement the methods described in the webinar. A final discussion is provided on how to introduce the methods into a company.

Why you should Attend: All manufacturing and development companies perform testing and/or inspections that involve concluding whether or not a product or lot is acceptable vs. design or QC specifications. Such test/inspections may occur during design verification/validation or during incoming or final QC.

The most informative method for analyzing the data that results from such activities is the calculation of the product's or lot's "reliability" at a chosen "confidence" level (where "reliability" means "in-specification"). Such a method produces information that is more valuable than simply that the given product or lot "passed" (as is the case when "AQL Attribute Sampling Plans" are used) or a % in-specification statement without any corresponding confidence statement (as is the case with AQL Variables Sampling Plans and with Process Capability calculations). The output of a "Confidence/Reliability" calculation is a definitive statement that the given product or lot has a specific % in-specification, which conclusion we can state with a specific level of confidence (e.g., 95% confidence of 99% reliability, or 90% confident of 93% reliability").

Areas Covered in the Session:

  • Regulatory Requirements
  • Vocabulary and Concepts
  • Attribute Data
  • Normal Data
  • Normal Probability Plotting
  • Non-Normal Data that can be normalized
  • Reliability Plotting (for data that cannot be normalized)
  • Implementation Recommendations

Who Will Benefit:
  • QA/QC Supervisor
  • Process Engineer
  • Manufacturing Engineer
  • QA/QC Technician
  • Manufacturing Technician
  • R&D Engineer


Speaker Profile
Michael Brodsky has been an Environmental Microbiologist for more than 41 years. He is a Past President of the Ontario Food Protection Association and AOAC International.

He serves as Chair for the AOAC Expert Review Committee for Microbiology, as a scientific reviewer in Microbiology for the AOAC OMA and the AOAC Research Institute, as a reviewer for Standard Method for the Examination of Water and as a chapter editor on QA for the Compendium of Methods in Microbiology. He is also a lead auditor/assessor in microbiology for the Canadian Association for Laboratory Accreditation (CALA) and is a member of the Board of Directors.


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