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Design Validation should ensure that product performance, quality, and reliability requirements are met.
In order to have high confidence that products will perform as intended, enough data must be collected and analyzed using various statistical methods.
Selecting appropriate sample sizes often vexes many practitioners. Testing only a few units does not provide a high level of confidence that performance requirements will be consistently met. Testing too many units may be unnecessarily expensive and can lead to misleading conclusions.
Statistical Methods are typically used to ensure that product performance, quality, and reliability requirements are met during the Design Validation phase of product development.
This webinar discusses common elements of sample size determination and several specific sample size applications for various design validation activities including Reliability Demonstration/Estimation, Acceptance Sampling, and Hypothesis Testing. Numerous examples are provided to illustrate the key concepts and applications.
Why should you Attend: Sample sizes have a significant impact on the uncertainty in estimates of key process performance characteristics. To have high confidence in results, sufficient sample sizes must be used.
Potential problems should be uncovered during Design Validation, prior to launching a product. Failure to do so may result in customer dissatisfaction, excessive warranty, costly recalls, or litigation.
Participants in the webinar will be able to understand the impact of sample sizes on the results from various statistical analysis methods commonly used during Design Validation.
Areas Covered in the Session: