Enter your shift time and planned stops
Start with the total shift length (e.g. 480 min for 8 hours) and subtract scheduled breaks, meals, and planned maintenance. The remainder is your Planned Production Time β the denominator for Availability.
Availability, performance, quality, and the Six Big Losses β in one view.
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OEE is the gold-standard metric for measuring how productively a machine or work cell uses its planned production time. A score of 100% means every minute the line was scheduled to run, it ran at full speed producing only good parts β no breakdowns, no slow cycles, no scrap.
The metric was formalised by Seiichi Nakajima as part of Total Productive Maintenance (TPM) and later standardised in ISO 22400. It decomposes into three independent factors β Availability, Performance, and Quality β so you can pinpoint exactly where losses are happening and calculate the ROI of fixing them.
Most plants run between 40% and 60% OEE without realising it. World-class is 85%. Closing that gap by even 10 percentage points on a high-speed line often equals millions in hidden capacity unlocked with zero capital expenditure.
Quick facts
Start with the total shift length (e.g. 480 min for 8 hours) and subtract scheduled breaks, meals, and planned maintenance. The remainder is your Planned Production Time β the denominator for Availability.
Record every minute the machine was stopped unexpectedly: breakdowns, waiting for materials, tooling changes that ran over schedule. Subtract this from Planned Production Time to get Run Time.
Enter the machine's nameplate cycle time in seconds (e.g. 45 s/part), total pieces produced, and how many were defective. Performance compares actual output rate to the ideal rate; Quality measures the good-parts ratio.
The calculator shows OEE, each of the three factors as a percentage, and a loss breakdown in minutes β so you can see immediately whether Availability, Performance, or Quality is your largest improvement lever.
Steps to use the OEE Calculator: Enter your shift time and planned stops, Enter unplanned downtime, Enter ideal cycle time and output counts, Read your OEE and loss breakdown.
Run Time = Planned Production Time β Unplanned Downtime. Planned stops (breaks, scheduled maintenance) are excluded from both numerator and denominator β they are not losses.
Example: 405 min Γ· 450 min = 90.0%
Compares what the machine actually produced to the theoretical maximum it could have produced at nameplate speed. Capped at 100% β a figure above 1.0 means the ideal cycle time is set too slow.
Example: (45 s Γ 480 pcs) Γ· (405 min Γ 60) = 21 600 Γ· 24 300 = 88.9%
Good Pieces = Total Pieces β Defective Pieces. Any part that requires rework counts as a defect for this calculation.
Example: 460 Γ· 480 = 95.8%
The three factors multiply together. Because of this, a weakness in any single factor pulls down the total disproportionately β 90% Γ 89% Γ 96% β 77%, not 92%.
Example: 0.900 Γ 0.889 Γ 0.958 = 76.7%
Scenario
A machining cell runs an 8-hour shift (480 min) with 30 min of scheduled breaks, 45 min of unplanned downtime, an ideal cycle time of 45 seconds, 480 total pieces produced, and 20 defective pieces.
480 min shift β 30 min planned stops = 450 min
Planned Production Time = 450 min
450 min β 45 min unplanned downtime = 405 min Run Time. Availability = 405 Γ· 450 = 90.0%
Availability = 90.0%
(45 s Γ 480 pcs) Γ· (405 min Γ 60) = 21 600 Γ· 24 300 = 88.9%
Performance = 88.9%
480 β 20 defects = 460 good pieces. Quality = 460 Γ· 480 = 95.8%
Quality = 95.8%
Availability 90.0% Γ Performance 88.9% Γ Quality 95.8% = OEE 76.7%
OEE = 76.7%
The takeaway
An OEE of 76.7% is in the "good" range (75β85%). The largest loss is Performance (88.9%), suggesting the machine is running slower than its design speed β minor stops or reduced speed cycles are the most likely cause.
| Metric | Poor | Average | Good | Excellent |
|---|---|---|---|---|
| OEE Score | < 65% | 65β74% | 75β84% | β₯ 85% (world-class) |
| Availability | < 75% | 75β84% | 85β94% | β₯ 95% |
| Performance | < 70% | 70β84% | 85β94% | β₯ 95% |
| Quality | < 95% | 95β98% | 98β99% | β₯ 99.5% |
| Feature | Calcrux (Free) | Manual Spreadsheet | Siemens Opcenter / SAP ME |
|---|---|---|---|
| Instant OEE calculation | |||
| Three-factor breakdown (A, P, Q) | Manual | ||
| Six Big Losses breakdown in minutes | |||
| Performance-cap warning (bad cycle time) | |||
| Actionable warnings per factor | Varies | ||
| ISO 22400 compliant formulas | Depends | ||
| Cost | Free | Free | 500β5,000 per year |
Why it matters
Scheduled breaks and planned maintenance are not OEE losses. Adding them inflates unplanned downtime and understates Availability.
Fix
Track planned and unplanned stops separately. Only unplanned events reduce Availability.
Why it matters
The ideal cycle time must be the theoretical maximum speed (nameplate speed), not what the machine typically achieves. Using the average masks Performance losses.
Fix
Use the machine manufacturer's published cycle time or the fastest sustained rate observed under good conditions.
Why it matters
Parts that need rework also represent lost capacity. OEE Quality must count all first-pass failures, not just scrapped pieces.
Fix
Count every piece that leaves the station without meeting spec on the first pass, even if it is reworked later.
Why it matters
A simple average of OEE scores is mathematically incorrect when shifts have different planned production times.
Fix
Compute OEE per shift, then calculate a weighted average using each shift's Planned Production Time as the weight.
Why it matters
A 95% OEE on a non-bottleneck machine is irrelevant. Over-producing fast runs up WIP inventory and can actually harm flow.
Fix
Focus OEE improvement efforts on the constraint machine (the bottleneck) first. Raising OEE on non-constraints rarely increases throughput.
Because OEE is multiplicative, the factor furthest from 100% gives the largest absolute gain when improved. If Availability is 70% and Performance is 95%, a 10-point Availability gain is worth far more than a 10-point Performance gain.
Shift-end OEE is useful for trending, but live OEE lets operators intervene during the shift. Even a simple downtime button on the machine panel dramatically improves data quality and response time.
Rolling out OEE tracking plant-wide at once creates data-quality problems and change-resistance. Pick your top bottleneck or highest-cost machine, get OEE right there, then expand.
A Performance score above 100% (caught by this calculator's capped-performance warning) is a sign your ideal cycle time is set too slow. Correct it before sharing OEE reports β otherwise every subsequent analysis is wrong.
OEE tells you how much you are losing. A downtime Pareto tells you why. Together they let you size an improvement project β calculate the value of the top three downtime causes and prioritise accordingly.
The OEE Calculator works across every stage of the workflow.
Track shift-by-shift OEE to spot deteriorating availability before it becomes a major breakdown, and share a clear metric with the maintenance team.
Quantify the current-state losses in a VSM (Value Stream Map) and build a business case for a TPM or SMED project by showing the financial value of recovered capacity.
Compare OEE across work cells to identify which machine is the true production bottleneck and where capital investment or headcount will have the highest ROI.
Run a quick OEE assessment for a new client without needing their MES system β gather shift data in a conversation, enter it here, and show them their loss breakdown in minutes.
Learn how Availability, Performance, and Quality interact, and see why a weakness in one factor pulls the total OEE down disproportionately β ideal for TPM or lean manufacturing coursework.
Every important term you'll encounter in this calculator and the broader topic.
Everything you need to know about how the OEE Calculator works.
OEE (Overall Equipment Effectiveness) measures how much of your planned production time is truly productive. It multiplies Availability, Performance, and Quality to give a single percentage score for machine efficiency.
OEE = Availability Γ Performance Γ Quality. Each factor is a ratio from 0 to 1, so a result of 0.85 means 85% of planned production time generated good output at full speed.
85% is the widely cited world-class benchmark, originally from Seiichi Nakajima's Total Productive Maintenance work. It means 15% of planned production time is lost across all three factors. Few plants sustain it.
Ideal cycle time is the theoretical fastest time to produce one good unit β the machine's nameplate or design speed. Using a cycle time that is slower than actual capability will inflate your Performance score artificially.
Calculate OEE for each shift separately using that shift's actual downtime and output. Then compute a weighted average by planned production time across shifts. Do not simply average the percentages.
Planned stops (breaks, scheduled maintenance, changeovers) are excluded from OEE as they are not losses you can eliminate. Unplanned downtime (breakdowns, waiting, starved lines) counts against Availability.
The Six Big Losses are: (1) Equipment failure, (2) Setup and adjustment β both hit Availability; (3) Idling and minor stops, (4) Reduced speed β both hit Performance; (5) Process defects, (6) Reduced yield β both hit Quality.
Start a downtime log to find the top three failure causes, then apply preventive maintenance on those points. Even moving from reactive to time-based servicing typically adds 5β10 percentage points to Availability.
ISO 22400 (Manufacturing Operations Management KPIs) defines OEE and related metrics formally. This calculator follows the ISO 22400 definitions for Availability, Performance, and Quality.
OEE does not capture throughput rate, cost, or downstream bottlenecks. A single machine with 95% OEE may still constrain a line if it is the bottleneck. Use OEE alongside cycle-time and flow analysis for full picture.
OEE measures performance against Planned Production Time (scheduled hours only). TEEP (Total Effective Equipment Performance) measures against calendar time β 24 hours a day, 7 days a week β so it also captures schedule losses. OEE is the more common shop-floor metric.
Yes β fully free, no sign-up required, and calculated entirely in your browser. The ISO 22400 formulas apply to discrete manufacturing, process manufacturing, packaging, and assembly lines worldwide. The inputs and outputs are unit-neutral.
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