Acceptance Sampling Plans for Process Validation and Production Lot Monitoring
Speaker: Steven Wachs
Speaker Designation: Vice President & Principal Statistician, Integral Concepts, Inc.
Speaker: Steven Wachs
Speaker Designation: Vice President & Principal Statistician, Integral Concepts, Inc.
This webinar covers Acceptance Sampling plans for process validation and production lot acceptance.
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.
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 to 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.
The information gained in the webinar will allow you to develop statistically sound sampling plans that manage the risks inherent when making decisions based on sample data.
Learning objectives include:
This webinar will provide valuable insights to:
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.
