mfg-oee-analysis

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Calculate and diagnose Overall Equipment Effectiveness (OEE) by decomposing into Availability, Performance, and Quality rates. Use this skill when the user needs to measure production line efficiency, identify equipment losses, benchmark manufacturing performance, or justify capital investment — even if they say 'why is our output low', 'machine utilization report', 'production efficiency', or 'how much capacity are we losing'.

asgard-ai-platform By asgard-ai-platform schedule Updated 4/10/2026

name: "mfg-oee-analysis" description: "Calculate and diagnose Overall Equipment Effectiveness (OEE) by decomposing into Availability, Performance, and Quality rates. Use this skill when the user needs to measure production line efficiency, identify equipment losses, benchmark manufacturing performance, or justify capital investment — even if they say 'why is our output low', 'machine utilization report', 'production efficiency', or 'how much capacity are we losing'." metadata: category: "WP-03 製造業" tags: ["manufacturing", "oee", "production-efficiency"]

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
Install via CLI
npx skills add https://github.com/asgard-ai-platform/skills --skill mfg-oee-analysis
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