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mfg-oee-analysis

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OEE Analysis

OEE分析

Framework

框架

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.
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

三大核心因素

FactorFormulaMeasuresLoss Categories
AvailabilityRun Time / Planned Production TimeUptime vs downtimeEquipment failures, changeovers, material shortages
Performance(Ideal Cycle Time × Total Count) / Run TimeActual speed vs design speedMinor stops, slow running, idling
QualityGood Count / Total CountYield, first-pass qualityDefects, rework, scrap, startup rejects
因素公式衡量指标损失类别
Availability运行时间 / 计划生产时间运行时间 vs 停机时间设备故障、换产、物料短缺
Performance(理想周期时间 × 总产量) / 运行时间实际速度 vs 设计速度小幅停机、低速运行、空转
Quality合格产量 / 总产量良率、一次合格率次品、返工、报废、启动阶段废品

Six Big Losses (mapped to OEE factors)

六大损失（对应OEE因素）

LossOEE FactorExample
1. Equipment failureAvailabilityMachine breakdown, unplanned repair
2. Setup & changeoverAvailabilityProduct changeover, die change, cleaning
3. Idling & minor stopsPerformanceSensor blockage, jam clearing, small adjustments
4. Reduced speedPerformanceRunning below rated speed due to wear or material
5. Process defectsQualityIn-process rejects, rework
6. Startup rejectsQualityScrap during warm-up, first-article failures
损失类型OEE因素示例
1. 设备故障Availability机器故障、非计划性维修
2. 换产与调试Availability产品切换、模具更换、设备清洁
3. 空转与小幅停机Performance传感器堵塞、卡料清理、小幅调整
4. 速度损失Performance因设备磨损或物料问题导致低于额定速度运行
5. 制程次品Quality制程内废品、返工
6. 启动阶段废品Quality预热阶段报废、首件不合格

Calculation Example

计算示例

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%
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

诊断步骤

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
阶段1： 计算每条生产线/每台设备的OEE 阶段2： 识别最弱的核心因素（可用率、性能率或合格率） 阶段3： 对该因素下的损失进行帕累托分析（哪项具体损失占比最大？） 阶段4： 对主要损失进行根本原因分析（5Why法、鱼骨图） 阶段5： 实施改进并重新测量

Benchmarks

基准参考

OEE LevelRatingTypical
> 85%World-classTop manufacturers
60-85%TypicalRoom for improvement
40-60%LowSignificant losses, urgent action needed
< 40%CriticalEquipment or process fundamentally broken
OEE水平评级典型场景
> 85%世界级顶尖制造企业
60-85%常规水平存在改进空间
40-60%较低水平损失严重，需紧急处理
< 40%危急水平设备或制程存在根本性问题

Output Format

输出格式

markdown
undefined
markdown
undefined

OEE Report: {Production Line}

OEE Report: {Production Line}

OEE Summary

OEE Summary

FactorValueBenchmarkStatus
Availability{%}>90%🟢/🟡/🔴
Performance{%}>95%🟢/🟡/🔴
Quality{%}>99%🟢/🟡/🔴
OEE{%}>85%🟢/🟡/🔴
FactorValueBenchmarkStatus
Availability{%}>90%🟢/🟡/🔴
Performance{%}>95%🟢/🟡/🔴
Quality{%}>99%🟢/🟡/🔴
OEE{%}>85%🟢/🟡/🔴

Loss Breakdown

Loss Breakdown

LossMinutes Lost% of Total LossPriority
{loss type}{min}{%}1/2/3
LossMinutes Lost% of Total LossPriority
{loss type}{min}{%}1/2/3

Root Cause (Top Loss)

Root Cause (Top Loss)

{5 Whys or fishbone analysis}
{5 Whys or fishbone analysis}

Improvement Plan

Improvement Plan

ActionTarget ImpactTimelineOwner
{action}+{X%} OEE{weeks}{who}
undefined
ActionTarget ImpactTimelineOwner
{action}+{X%} OEE{weeks}{who}
undefined

Gotchas

注意事项

  • 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.
  • OEE是单台设备的指标，而非工厂级指标：工厂级OEE平均值会掩盖“一台设备OEE为95%、另一台为45%，最终平均为70%”的真实情况，应单独分析每台设备。
  • 计划停机时间需排除在外：OEE是针对计划生产时间计算损失的指标。预防性维护、无生产班次、计划停机等均不计入分母。
  • 100% OEE并非目标：这意味着零换产、零次品、全程满速运行。追求100%可能增加成本（如从不进行预防性维护），关键生产线目标应设为85%以上。
  • 数据采集是核心挑战：手动跟踪OEE准确性低，应投资自动化数据采集方案（传感器、MES系统集成）以获得可靠数据。

References

参考资料

  • For TPM (Total Productive Maintenance) methodology, see 
    references/tpm.md
  • For automated OEE data collection, see 
    references/oee-automation.md
  • 关于全面生产维护（TPM）方法论，请参阅
    references/tpm.md
  • 关于自动化OEE数据采集，请参阅
    references/oee-automation.md