OEE Calculator
SkillDev toolsOverall Equipment Effectiveness calculation and analysis skill with availability, performance, and quality tracking
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the OEE Calculator skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/business/operations/skills/oee-calculator/SKILL.md and read by ahel’s review.
Overview
The OEE Calculator skill provides comprehensive capabilities for calculating and analyzing Overall Equipment Effectiveness. It supports availability, performance, and quality tracking, six big loss categorization, and world-class benchmarking.
Capabilities
- Availability calculation
- Performance rate tracking
- Quality rate measurement
- OEE trending and dashboards
- Six big loss categorization
- Pareto of losses
- Improvement target setting
- World-class benchmarking
Used By Processes
- LEAN-001: Value Stream Mapping
- SIX-002: Statistical Process Control Implementation
- CI-003: Benchmarking Program
Tools and Libraries
- MES integration
- OEE software
- Real-time dashboards
- Data collection systems
Usage
skill: oee-calculator
inputs:
equipment: "CNC Machine 5"
period: "2026-01-15"
shift_data:
planned_production_time: 480 # minutes
downtime:
- type: "breakdown"
minutes: 30
- type: "changeover"
minutes: 20
ideal_cycle_time: 0.5 # minutes per unit
total_count: 800 # units
good_count: 780 # units
outputs:
- oee_score
- availability
- performance
- quality
- loss_breakdown
- improvement_opportunities
- trend_analysis
OEE Calculation
Formula
OEE = Availability x Performance x Quality
Where:
Availability = Run Time / Planned Production Time
Performance = (Total Count x Ideal Cycle Time) / Run Time
Quality = Good Count / Total Count
Example Calculation
Planned Production Time: 480 minutes
Downtime: 50 minutes
Run Time: 430 minutes
Ideal Cycle Time: 0.5 minutes
Total Count: 800 units
Good Count: 780 units
Availability = 430 / 480 = 89.6%
Performance = (800 x 0.5) / 430 = 93.0%
Quality = 780 / 800 = 97.5%
OEE = 89.6% x 93.0% x 97.5% = 81.3%
Six Big Losses
| Loss Category | OEE Factor | Examples |
|---|---|---|
| Breakdowns | Availability | Equipment failures |
| Setup/Adjustments | Availability | Changeovers, warm-up |
| Small Stops | Performance | Jams, minor issues |
| Reduced Speed | Performance | Running below ideal rate |
| Startup Rejects | Quality | Scrap during start-up |
| Production Rejects | Quality | In-process defects |
OEE Benchmarks
| OEE Level | Classification | Typical Range |
|---|---|---|
| World Class | Best in class | 85%+ |
| Good | Above average | 70-85% |
| Average | Typical | 60-70% |
| Low | Needs improvement | 40-60% |
| Poor | Significant issues | <40% |
World-Class Targets
| Factor | World Class | Typical |
|---|---|---|
| Availability | >90% | 85% |
| Performance | >95% | 90% |
| Quality | >99.9% | 98% |
| OEE | >85% | 60% |
Loss Analysis Process
- Collect accurate loss data
- Categorize by six big losses
- Create Pareto chart
- Focus on top losses
- Apply appropriate methodology
- Track improvement
Integration Points
- Manufacturing Execution Systems
- PLC/SCADA systems
- Quality Management Systems
- Maintenance management (CMMS)
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
oee-calculator- Source
- github.com/a5c-ai/babysitter