Sample Size Determination for Design Validation Activities

Duration: 75 Minutes
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.
Determining Sample Size for Design Validation
Instructor: Steven Wachs
Product ID: 506241
Objectives of the Presentation
  • 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)
Why Should you Attend
Design Validation should ensure that product performance, quality, and reliability requirements are met. In order to have high confidence that those products will perform as intended, enough data must be collected and analyzed using various statistical methods. 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.

This webinar discusses many issues present in any sample size determination. It will highlight several common applications that require an appropriate sample size determination including Reliability Demonstration/Estimation, Estimating proportions, Acceptance Sampling for Lot Disposition, and Hypothesis Testing. Numerous examples are provided to illustrate the key concepts and applications.

Who will Benefit
The target audience includes personnel involved in product/process development and manufacturing
  • 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
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Instructor Profile:
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.
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