Manufacturing: Confidence-Reliability Calculations and Statistically Valid Sample Sizes
Manufacturing, Maths, Statistics,Business
NetZealous LLC
Summary
- Certificate of completion - Free
- Tutor is available to students
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.
Description
Why should you 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 is this course for?
- QA/QC Supervisor
- Process Engineer
- Manufacturing Engineer
- QC/QC Technician
- Manufacturing Technician
- R&D Engineer
Questions and answers
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Certificates
Certificate of completion
Digital certificate - Included
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Legal information
This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.