All measurement systems assessment methods are design of experiments.  Every measurement system can be evaluated and its variation estimated.  Exceed AIAG MSA requirements with hands-on applied training.  Participants will need to bring a laptop with a recent version of Minitab.  Workshop files will be provided that show the Minitab data structure with step by step instructions to perform the analysis and class discussions to understand what the analysis results mean.  Measurement variation can be produced from any measurement system including single observation destructive tests.  Measurement variation is the error term from any design experiment.

Measurement System Assessment Overview

• Understanding a Measurement System: Gage Repeatability and Reproducibility (GRR)
• Precision, Accuracy, and Calibration
• Linearity
• Stability
• Operator, Gage, Methods, Part, and other Components of Measurement Variation
• The measurement process and controllability
• All Gage Repeatability and Reproducibility Studies are Design Experiments

The two-factor GRR: Within, between, and operator-gage interaction variation

• GRR as a percent of process: When used for process capability studies
• GRR as a percent of specification: When used for sorting parts

Long-Term Measurement Process Capability Assessment

• Short-Term X and Rm Charts
• Xbar-R or Xbar-S Charts on Master Parts

Advanced methods and the ISO Guide to Expression of Uncertainty in Measurement

• Destructive Testing
• Testing changes next measurement reading (nested)
• Underlying system changes (e.g. heating, moving-cannot read twice, etc.)
• Reference Measurement System
• Intra-Class Correlation
• The Discrimination Ratio
• Developing Confidence Limits for the True Value
• Modeling the Attribute Gage System (go/no-go)
• Understanding Components of Variation
• Using Analysis of Variance (ANOVA) Gage RR

Identifying Interaction GRR Components

• Interpretation Using Confidence Intervals
• Within Part Variation
• Between gage variation
• Between user variation
• Advanced Studies Using ANOVA
• Multiple Measurement Systems
• Single observation Measurement Systems
• MSA and Nested Samples
• Multiple Components of Reproducibility Variation