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Speaker: Steven Wachs
Speaker Designation: Vice President & Principal Statistician, Integral Concepts, Inc.
The process of design validation is a crucial step in ensuring the quality and effectiveness of a product. However, determining the appropriate sample size for design validation activities can be challenging. A sample size that is too small may not provide sufficient data to make accurate conclusions, while a sample size that is too large can be costly and time-consuming.
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. By the end of the webinar, participants will have a better understanding of how to determine the appropriate sample size for design validation activities, and how to ensure that the sample size selected is sufficient to make accurate conclusions.
Design Validation should ensure that product performance, quality, and reliability requirements are met.
To ensure that products perform as intended, it is crucial to collect and analyze enough data using statistical methods. The sample size plays a critical role in determining the level of uncertainty in estimates of key process performance characteristics. It is imperative to use sufficient sample sizes to have confidence in the results. Design Validation is an essential step in identifying potential issues before launching a product. Failure to do so may lead to customer dissatisfaction, expensive recalls, legal disputes, and excessive warranty costs.
The webinar covers various aspects related to determining the appropriate sample size. 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 practical applications.
The objective of the webinar is to educate participants on the importance of sample sizes in design validation and how it impacts the evaluation of product performance, quality, and reliability. The webinar aims to provide insights into the statistical methods and tools used to determine appropriate sample sizes for validation testing, and how to interpret results accurately.
The target audience includes personnel involved in product/process development and manufacturing -
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He 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.
Mr. Wachs 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. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.
He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.
