Process Capability Analysis by means of Confidence Reliability Calculations

Author: Adam Fleming

Process Capability Analysis by means of Confidence Reliability Calculations

Testing and/or inspections with the intention of concluding whether or not a product or lot is acceptable vis-à-vis design or QC specifications is something that organizations in the manufacturing and development areas perform regularly. Typically, these tests or inspections happens during design verification/validation or during incoming or final QC.

Calculating the product's or lot's "reliability" at a chosen "confidence" level, where "reliability" means "in-specification" is considered the most informative method for analyzing the data that results from such activities. The information such a method produces 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 is issued without any corresponding confidence statement (as is the case with AQL Variables Sampling Plans and with Process Capability calculations).

As a result, the output derived from a "Confidence/Reliability" calculation is a definitive statement that the given product or lot has a specific percentage in-specification. This conclusion can be stated with a specific level of confidence (e.g., 95% confidence of 99% reliability, or 90% confident of 93% reliability").

More about process capability analysis can be learnt at a webinar that is being organized on February 26 by Compliance4All, a leading provider of professional training for all the areas of regulatory compliance.

For this webinar, Compliance4All brings Michael Brodsky, a noted an Environmental Microbiologist, as the expert. Please log on to Compliance4all to derive valuable learning on the concept of process capability analysis.

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At this webinar, Michael will discuss calculating "confidence/reliability" in the backdrop of the relevant regulatory requirements. He will explain the vocabulary and the basic concepts involved in process capability analysis.

He will then explain in detail how to calculate the following:

  • 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.

Using spreadsheets as examples of how to implement the methods described in the session, the expert will wind up with learning on how to introduce these methods into a company.

He will cover the following areas at this webinar:

  • 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
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About the expert: 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.