OEE Analysis

Framework

IRON LAW: OEE = Availability × Performance × Quality

OEE is a MULTIPLICATIVE metric. 90% × 90% × 90% = 72.9%, not 90%.
Each factor compounds the loss. World-class OEE is 85%+. Most plants
operate at 60-65%. Knowing the TOTAL is useless — you must decompose
to find which factor is dragging performance down.

The Three Factors

Factor	Formula	Measures	Loss Categories
Availability	Run Time / Planned Production Time	Uptime vs downtime	Equipment failures, changeovers, material shortages
Performance	(Ideal Cycle Time × Total Count) / Run Time	Actual speed vs design speed	Minor stops, slow running, idling
Quality	Good Count / Total Count	Yield, first-pass quality	Defects, rework, scrap, startup rejects

Six Big Losses (mapped to OEE factors)

Loss	OEE Factor	Example
1. Equipment failure	Availability	Machine breakdown, unplanned repair
2. Setup & changeover	Availability	Product changeover, die change, cleaning
3. Idling & minor stops	Performance	Sensor blockage, jam clearing, small adjustments
4. Reduced speed	Performance	Running below rated speed due to wear or material
5. Process defects	Quality	In-process rejects, rework
6. Startup rejects	Quality	Scrap during warm-up, first-article failures

Calculation Example

Planned Production Time: 480 min (8-hour shift)
Downtime (breakdowns + changeover): 60 min
Run Time: 420 min

Ideal Cycle Time: 1 min/unit
Total Units Produced: 380

Good Units: 360
Defective Units: 20

Availability = 420 / 480 = 87.5%
Performance = (1 × 380) / 420 = 90.5%
Quality = 360 / 380 = 94.7%

OEE = 87.5% × 90.5% × 94.7% = 75.0%

Diagnosis Steps

Phase 1: Calculate OEE for each production line/machine Phase 2: Identify the weakest factor (Availability, Performance, or Quality) Phase 3: Pareto the losses within that factor (which specific loss is biggest?) Phase 4: Root cause analysis on the top loss (5 Whys, fishbone) Phase 5: Improve and remeasure

Benchmarks

OEE Level	Rating	Typical
> 85%	World-class	Top manufacturers
60-85%	Typical	Room for improvement
40-60%	Low	Significant losses, urgent action needed
< 40%	Critical	Equipment or process fundamentally broken

Output Format

# OEE Report: {Production Line}

## OEE Summary
| Factor | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| Availability | {%} | >90% | 🟢/🟡/🔴 |
| Performance | {%} | >95% | 🟢/🟡/🔴 |
| Quality | {%} | >99% | 🟢/🟡/🔴 |
| **OEE** | **{%}** | **>85%** | 🟢/🟡/🔴 |

## Loss Breakdown
| Loss | Minutes Lost | % of Total Loss | Priority |
|------|-------------|----------------|---------|
| {loss type} | {min} | {%} | 1/2/3 |

## Root Cause (Top Loss)
{5 Whys or fishbone analysis}

## Improvement Plan
| Action | Target Impact | Timeline | Owner |
|--------|-------------|----------|-------|
| {action} | +{X%} OEE | {weeks} | {who} |

Gotchas

• OEE is per machine, not per plant: Plant-level OEE averages hide that one machine at 95% and another at 45% average to 70%. Analyze individually.
• Planned downtime is excluded: OEE measures losses against PLANNED production time. Scheduled maintenance, no-production shifts, and planned shutdowns are excluded from the denominator.
• 100% OEE is not the goal: It would mean zero changeovers, zero defects, running at max speed 100% of the time. Pursuing 100% can increase costs (e.g., never doing preventive maintenance). Target 85%+ for critical lines.
• Data collection is the real challenge: Manual OEE tracking is inaccurate. Invest in automated data collection (sensors, MES integration) for reliable measurement.

References

• For TPM (Total Productive Maintenance) methodology, see references/tpm.md
• For automated OEE data collection, see references/oee-automation.md