Gage R&R Analyzer

Overview

The Gage R&R Analyzer skill provides comprehensive capabilities for conducting Measurement System Analysis (MSA) studies. It supports Gage R&R study design, ANOVA-based variance decomposition, and measurement system adequacy assessment following AIAG guidelines.

Capabilities

• Gage R&R study design
• ANOVA variance decomposition
• Repeatability analysis
• Reproducibility analysis
• %GRR calculation
• Number of distinct categories
• Measurement bias and linearity
• Acceptance criteria evaluation

Used By Processes

• SIX-004: Measurement System Analysis
• SIX-002: Statistical Process Control Implementation
• QMS-003: Quality Audit Management

Tools and Libraries

• Minitab API
• Statistical analysis packages
• Calibration management systems
• Data collection tools

Usage

skill: gage-rr-analyzer
inputs:
  study_type: "crossed"  # crossed | nested
  operators: 3
  parts: 10
  trials: 3
  measurements:
    - operator: "A"
      part: 1
      trial: 1
      value: 10.2
    # ... additional measurements
  tolerance: 1.6  # USL - LSL
outputs:
  - variance_components
  - percent_grr
  - percent_tolerance
  - ndc
  - acceptance_decision
  - detailed_report

Variance Components

Component	Source	Description
Part-to-Part	Process	Variation between parts
Repeatability	Equipment	Variation from repeated measurements
Reproducibility	Operator	Variation between operators
Part x Operator	Interaction	Operator effect varies by part

Acceptance Criteria (AIAG Guidelines)

%GRR	Decision
< 10%	Acceptable
10% - 30%	Marginal, may be acceptable
> 30%	Unacceptable

Number of Distinct Categories (ndc)

ndc = 1.41 * (Part Variation / GRR)

Interpretation:
- ndc >= 5: Adequate measurement system
- ndc < 5: Measurement system needs improvement

Study Design Requirements

Study Type	Minimum Parts	Minimum Operators	Minimum Trials
Standard	10	3	2-3
Attribute	30	3	3
Destructive	Use nested design	3	1

Integration Points

• Calibration management systems
• Quality Management Systems
• Statistical analysis software
• Training management systems