Attendees of this webinar will learn statistically valid methods for using small sample sizes and for using lots as few as 3 when validating processes or products.
The focus of this webinar is on providing the information needed for attendees to understand the concepts of risk in relation to process validation and to be able to compute sample sizes and lot sizes according the desired or required specification criteria or the process or product.
Why Should You Attend:
Regulatory and certification bodies have requirements for the validation of processes. 21 CFR Part 820.75 (a) Process validation states,” Where the results of a process cannot be fully verified by subsequent inspection and test, the process shall be validated with a high degree of assurance and approved according to established procedures.” Additionally, ISO 9001:2008 7.5.2 Validation of processes for production and service provision states “The organization shall validate any processes for production and service provision where the resulting output cannot be verified by subsequent monitoring or measurement and, as a consequence, deficiencies become apparent only after the product is in use or the service has been delivered.”
Attend this webinar to understand the concepts of risk about process validation and learn to compute sample sizes and lot sizes according to the desired or required specification criteria or the process or product. 100% testing in most manufacturing processes would require 100% destruction of the product being made. Therefore it is important to know the minimum amount of product to sample from a minimum number of lots in order to preserve inventory while minimizing risk (such as loss of product, consumer risk of defectives, etc.)
Areas Covered in the Webinar:
Who Will Benefit:
Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California.
Elaine earned her B.S. in Statistics at UC Riverside and received her Master’s Certification in Applied Statistics from Texas A&M.
Elaine is a member in good standing with the American Statistical Association and a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.
Elaine has designed the methodology and analyzes data for numerous studies in the clinical, biotech, and health care fields. Elaine has also works as a contract statistician with private researchers and biotech start-ups as well as with larger companies such as Allergan, Nutrisystem and Rio Tinto Minerals. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals.
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