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
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
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 you should 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:
- Populations, Samples, Data Types, and Basic Statistics
- Common Elements of Sample Size Determination
- Design Validation Applications
- Sample Sizes for Reliability Demonstration (Pass/Fail Outcomes)
- Sample Sizes for Reliability Estimation
- Sample Sizes for Estimating Proportion Failing (Pass/Fail Test Outcomes)
- Sample Sizes for Acceptance Sampling / Lot Disposition
- Other Common Sample Size Applications (Hypothesis Testing, Equivalence Testing)
Who Will Benefit:
- Quality Personnel
- Product Design/Development personnel
- Manufacturing Personnel
- Operations / Production Managers
- Production Supervisors
- Supplier Quality personnel
- Quality Engineering
- Quality Assurance Managers, Engineers
- Process or Manufacturing Engineers or Managers