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.
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.
This webinar discusses many issues present in any sample size determination. The webinar also discusses 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.
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 Webinar:The target audience includes personnel involved in product/process development and manufacturing
Steven WachsPrincipal Statistician, Integral Concepts, Inc
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.
Registrants may cancel up to two working days prior to the course start date and will receive a letter of credit to be used towards a future course up to one year from date of issuance. FDATrainingAlert would process/provide refund if the Live Webinar has been cancelled. The attendee could choose between the recorded version of the webinar or refund for any cancelled webinar. Refunds will not be given to participants who do not show up for the webinar. On-Demand Recordings can be requested in exchange.
Webinar may be cancelled due to lack of enrolment or unavoidable factors. Registrants will be notified 24hours in advance if a cancellation occurs. Substitutions can happen any time.
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