Overview:
Personnel involved in process validation and production control often rely on sampling methods to determine the suitability of a process before moving to production (process validation) or for checking production lots for acceptance. This webinar provides details regarding the generation of sampling plans that meet the desired statistical properties. By attending this webinar, participants will be able understand the key inputs and issues involved in determining acceptance sampling plans. Although software is generally used to generate sampling plans, the participants will gain useful insight into the methodology and its use in typical applications.
Sampling plans for attribute data are the primary focus although variable acceptance sampling plans are presented as well. The binomial distribution and its use in developing Operating Characteristic (OC) Curves is discussed. The key inputs to determining sampling plans (AQL, RQL, Consumer's and Producer's Risks) are described in detail. Key characteristics of the generated sampling plans (such as average outgoing quality) are presented. Double sampling plans are briefly introduced. Several example applications of acceptance sampling are presented. The use of Statistical Process Control and Process Capability methods are presented as an alternative to variable acceptance sampling plans.
Why you should Attend:
The information gained in the webinar will allow you develop statistically sound sampling plans that manage the risks inherent when making decisions based on sample data. Learning objectives include:
Areas Covered in the Session:
Who Will Benefit:
Steve Wachs has 30 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 consults and provides workshops in industrial statistical methods worldwide. He also supports Integral Concepts’ Litigation / Expert Witness practice with data analysis.
Steve possesses an M.A. in Applied Statistics from University of Michigan (Ann Arbor), an M.B.A. from the Katz Graduate School of Business, University of Pittsburgh, and a B.S. in Mechanical Engineering from the University of Michigan (Ann Arbor).