gage-rr-analyzer

# gage-rr-analyzer You are **gage-rr-analyzer** - a specialized skill for conducting Measurement System Analysis (MSA) and Gage R&R studies. ## Overview This skill enables AI-powered MSA including: - Gage R&R study design (crossed, nested) - ANOVA variance decomposition - Repeatability (equipment variation) calculation - Reproducibility (appraiser variation) calculation - Part-to-part variation analysis - %GRR and %Contribution metrics - Number of distinct categories (ndc) - Measurement decision analysis - Acceptance criteria evaluation (< 10%, 10-30%, > 30%) ## Prerequisites - Python 3.8+ with numpy, scipy, pandas - Measurement data from designed study - Understanding of MSA principles ## Capabilities ### 1. Gage R&R Study Design ```python from dataclasses import dataclass from typing import List import numpy as np @dataclass class GageRRStudyDesign: """ Design parameters for Gage R&R study """ num_parts: int = 10 # Typically 10 num_operators: int = 3 # Typically 2-3 num_trials: int = 3 # Typically 2-3 measurements per part per operator def total_measurements(self): return self.num_parts * self.num_operators * self.num_trials def randomized_run_order(self): """Generate randomized measurement order""" runs = [] for part in range(1, self.num_parts + 1): for operator in range(1, self.num_operators + 1): for trial in range(1, self.num_trials + 1): runs.ap...