Root Cause Analyzer

Overview

The Root Cause Analyzer skill provides comprehensive capabilities for systematic root cause identification and verification. It supports multiple analysis methods including 5 Whys, Ishikawa diagrams, fault tree analysis, and statistical hypothesis testing.

Capabilities

• 5 Whys facilitation
• Ishikawa (fishbone) diagram creation
• Fault tree analysis (FTA)
• Hypothesis formulation
• Chi-square testing
• Correlation analysis
• Pareto chart generation
• Root cause verification

Used By Processes

• SIX-005: Root Cause Analysis
• QMS-005: FMEA Facilitation
• CI-002: A3 Problem Solving

Tools and Libraries

• Cause analysis tools
• Statistical testing libraries
• Visualization platforms
• Collaboration tools

Usage

skill: root-cause-analyzer
inputs:
  problem_statement: "25% increase in customer complaints for product X"
  analysis_method: "fishbone"  # 5_whys | fishbone | fta | is_is_not
  data:
    defect_counts_by_category:
      materials: 45
      methods: 23
      machines: 67
      manpower: 12
      measurement: 8
      environment: 5
  hypothesis_to_test: "Machine wear is causing increased defects"
outputs:
  - root_cause_diagram
  - potential_causes
  - verified_root_causes
  - pareto_analysis
  - statistical_verification
  - recommendations

Analysis Methods

5 Whys

Ask "Why?" iteratively to drill down to root cause:

1. Why did the problem occur?
2. Why did that happen?
3. Why did that happen?
4. Why did that happen?
5. Why did that happen?

Ishikawa (Fishbone) Categories

• Man (Manpower) - Training, skills, fatigue
• Machine - Equipment, tools, technology
• Method - Procedures, processes, policies
• Material - Raw materials, consumables
• Measurement - Inspection, calibration
• Mother Nature (Environment) - Temperature, humidity, conditions

Fault Tree Analysis

• Top event (undesired outcome)
• AND gates (all inputs required)
• OR gates (any input sufficient)
• Basic events (root causes)

Verification Techniques

Technique	Use Case
Chi-square test	Categorical data relationships
Correlation analysis	Continuous variable relationships
Regression	Predictive relationships
Designed experiments	Controlled cause-effect testing
Pareto analysis	Vital few vs. trivial many

Integration Points

• Quality Management Systems
• Corrective action systems
• Statistical analysis tools
• Knowledge management systems