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Process Capability for Normal and Non-Normal Data

Monday June 11 2018  08:00 AM PDT | 11:00 AM EDT

Training Duration = 90 Min                    Sponsored by Compliance Online

Click Here to register $349.00

Click Here to register and receive recording $199.00

The webinar will provide methods for assessing and understanding Process Capability. Participants should be able to immediately apply the methods presented.

Why Should You Attend:

This webinar discusses methods for estimating process capability for both normal and non-normal data. Pre-requisites for estimating process capability (e.g. establishing process stability) are discussed first. Distributions are briefly described and methods for estimating ppm levels are presented.

The use and limitations of common process capability indices (e.g. Cpk and Ppk) are discussed. It is vital that appropriate methods are used for estimating capability when the data is not well described by a normal distribution. Failure to do so often results in overly optimistic process capability estimates. Methods for testing for normality are discussed.

Both transformations and distribution fitting are presented as methods to assess capability for non-normal data. The webinar includes several examples to illustrate the methods.

Learning Objectives:

  • Understand pre-requisites for assessing process capability
  • Apply methods for estimating capability for both normal and non-normal data
  • Test data for normality
  • Understand and interpret process capability indices

Areas Covered

  • Process Stability and Process Capability
  • Methods for Assessing Process Capability
  • Estimating PPM
  • Calculating and Interpreting Capability Indices (Cp, Cpk, Pp, Ppk, Cpm)
  • Estimating uncertainty (confidence intervals)
  • Shortcomings of Capability Indices
  • Testing for Normality
  • Methods for handling Non-Normal Data (Distribution fitting, transforming data)


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.