Measurement Systems Analysis (MSA)

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Organizations use data every day to make decisions. Good data allows us to make good decisions; on the other hand, bad data typically leads to bad decisions. So how do we know if our data is good?

This is where measurement system analysis (MSA) comes in. MSA is a combination of tools and techniques used to determine if a measurement system is acceptable for its purpose.

In this workshop, participants will learn MSA terminology, tools, and techniques and will perform a complete variable gauge reproducibility and repeatability (R&R) study. Applied to their own workplace, this new knowledge and skills will allow participants to validate their own measurement system through proven methods.


  • Describe the goals and benefits of measurement system analysis (MSA).
  • Define “variation” and explain the difference between common cause and special cause variation.
  • Explain the characteristics of a “good” measurement system.
  • Explain the importance of the resolution of a measurement device.
  • Explain the purpose of measurement device calibration and how it relates to measurement system performance.
  • Define “traceability” in the context of device calibration.
  • Explain the purpose and steps of a variable gauge R&R study.
  • Perform a variable gauge R&R study.
  • Explain the purpose and steps of an attribute agreement analysis.
  • Perform an attribute agreement analysis.

Intended audience: Individuals in manufacturing and quality roles who have existing knowledge of statistical process control tools and techniques used in manufacturing or those who have completed Purdue MEP's workshop Statistical Process Control.


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