Overview:
Important measurement system characteristics include discrimination, accuracy, precision (repeatability and reproducibility), linearity, and stability. Techniques exist to assess measurement systems for each of these important characteristics. Skipping such assessments can lead to the use of measurement systems that are not capable of monitoring process variation or, in extreme cases, even of distinguishing between conforming and non-conforming products.
In short, validating measurement systems is an important pre-requisite to relying on data. Measurement systems must be properly assessed to minimize risk and comply with customer and regulatory requirements. While most companies perform some aspects of MSA, such as Gage Repeatability & Reproducibility studies, we often observe inadequate assessments of measurement systems. In addition to an overview of MSA methods, this webinar identifies many improvements that most companies can make to their measurement systems assessments.
Why you should Attend:
Areas Covered in the Session:
This program will discuss numerous ways in which companies can improve their Measurement Systems Assessments:
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).