Editorial

Objectives

This webinar focus the relevant vocabulary, basic concepts, best practices and the relevant regulatory requirements of confidence/reliability calculation.

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, and the use of confidence limits on Cpk (the classic value calculated to quantitate process capability).

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 classic Process Capability calculations)

Program

• Areas Covered in the Webinar:

• Regulatory Requirements
• Vocabulary and Concepts
• Process Capability Indices
• Attribute Data
• Normal Data
• How to Evaluate for Normality
• How to Transform Non-Normal Data into Normality
• MTTB calculations