First Pass Yield: Formula, An Example and the Link to OEE Quality
What is first pass yield?
First pass yield is the percentage of units that come out good the first time, without scrap, repair, or rework. A high FPY means the process makes usable parts on the first attempt. A low FPY means the line spends time and money correcting defects after production has already happened.
First pass yield formula
FPY = Good units that pass the first time ÷ Total units started × 100
Use this formula when you want to see how much output is right before rework hides the problem.
For example, if a line starts 340 units and 322 units pass the first time:
FPY = 322 ÷ 340 × 100 = 94.7%
That means 17.3 units per 340 need attention, on average, before the day’s output can be considered clean.
FPY matters because quality loss is visible money. Scrap uses material. Rework uses labour. Extra inspection uses time that could have gone into the next order.
How to calculate first pass yield
You calculate first pass yield by counting the units that pass quality checks the first time, then dividing that number by the total units that entered the process.
Here is a simple window line example.
A window line makes 340 units in one day:
322 units pass first time.
10 units need rework before shipment.
8 units are scrapped.
340 units entered the process.
The first pass yield calculation uses only the 322 first-time-good units.
FPY = 322 ÷ 340 × 100 = 94.7%
The final yield can look higher if the 10 reworked units are accepted later.
Final accepted yield = 332 ÷ 340 × 100 = 97.6%
That gap is important. The customer may still receive 332 good windows, but the factory paid for rework on 10 units and lost material on 8 units.
FPY shows the first-time quality of the process. Final yield shows what survived after extra work.
For a production manager, FPY is the cleaner improvement signal. It tells you where the process creates defects before rework smooths the report.
FPY vs quality rate in OEE
FPY and the OEE quality rate both compare good output against total output, but they are used for slightly different jobs.
In the OEE calculation, Quality is usually calculated as:
OEE Quality Rate = Good Count ÷ Total Count × 100
OEE then combines the three components:
OEE = Availability × Performance × Quality
Here is the practical difference on the shop floor:
| Metric | What it measures | What it is best for |
|---|---|---|
| First pass yield | Units that pass the first time without rework. | Finding process quality problems early. |
| OEE Quality Rate | Good count compared with total count for the OEE period. | Measuring how quality affects total equipment effectiveness. |
| Final yield | Units accepted after rework and correction. | Confirming shipment-ready output. |
If your OEE setup counts reworked units as good after final inspection, the OEE Quality Rate can look better than FPY.
That does not mean the process is healthy. Rework still consumes labour, machine time, inspection time, and material handling.
The best setup is to track good count, reject count, and rework count separately. Then FPY shows first-time quality, while OEE shows how quality losses affect the whole production day.
FPY across multiple process steps: rolled throughput yield in brief
Rolled throughput yield shows how first pass yield behaves across several process steps.
A line can have good FPY at each station and still lose a lot of output across the full route.
The formula is simple:
RTY = Step 1 FPY × Step 2 FPY × Step 3 FPY
Example for a three-step production flow:
Cutting FPY: 96%
Assembly FPY: 98%
Final inspection FPY: 95%
RTY = 0.96 × 0.98 × 0.95 = 0.894
That gives a rolled throughput yield of 89.4%.
Each process step looks acceptable on its own. Together, the full route loses more than 10 units per 100 before clean first-time output reaches the customer.
RTY is useful when defects move downstream. A small cutting issue can become an assembly delay. A small assembly issue can become final inspection scrap.
For SME manufacturers, this matters because people usually fix the defect where they find it. RTY helps you trace where the defect started.
What drives quality losses on an SME line
Quality losses on an SME line usually come from unstable process conditions, late defect detection, or unclear operator feedback.
The common drivers are easy to recognise once you measure them at the source:
Startup rejects after changeover: The first pieces after a setup change often expose wrong settings, material variation, or missing checks.
First-article scrap: The first accepted sample may take several attempts when settings are adjusted by feel instead of data.
Tool wear: A worn blade, drill, mould, or fixture can create defects before the operator sees the pattern.
Material changes: Wood, metal, plastic, and food materials can behave differently by batch, supplier, temperature, or humidity.
Manual recording: Paper logs and end-of-shift summaries miss defects that happen between checks.
Unclear defect reasons: “Bad part” does not tell a manager whether the cause was setup, material, machine condition, or operator instruction.
The biggest problem is timing.
If rejects are counted at the end of the shift, the team learns too late. The same defect can run for hours before anyone sees the pattern.
For FPY improvement, the first question is simple: Where did the first bad unit appear, and what changed right before it?
That question connects quality work to changeovers, maintenance, operator instructions, and planning.
Tracking good count vs total count automatically
Tracking good count and total count automatically means collecting production counts at the machine, then adding operator reason codes when rejects happen.
This is where FPY becomes useful day to day.
Manual FPY tracking usually breaks in three places:
Operators record totals after the shift, when details are already fuzzy.
Rework gets mixed into good output, which hides first-time failures.
Managers see the FPY number without the reason behind the loss.
GlobalReader is built to close those gaps with hardware and software together.
The hardware captures machine states and counts from the line. Operator lets the shop floor add the reason behind scrap, rejects, stops, and production changes.
Analytics then breaks losses down by shift, line, machine, and reason code. That makes FPY more than a spreadsheet number.
With automatic tracking, you can see:
Good count vs total count while the line is running.
Reject reasons before the end-of-shift report.
Quality impact on OEE next to availability and performance.
Trends by product, order, shift, or machine when the same defect repeats.
This matters on older machines too. GlobalReader includes retrofit hardware, so you do not need to replace equipment just to collect basic count and status data.
Start with the line where scrap hurts most. Prove the value there, then add Operator, Planner, Maintenance, Smart Factory, or Quality Control as the process grows.
If you want to see how real-time quality tracking works on a production line, try the GlobalReader free demo. No financial commitment, just a guided product demo you can explore yourself.
FAQ
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FPY measures units that pass the process the first time, with no repair, rework, or second inspection needed. It shows how clean the process is before correction work hides defects.
Yield is broader. Final yield can include units accepted after rework, so yield may look better than the first-time performance of the line.
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A good FPY depends on the product, process, and industry, so there is no single target that fits every factory. A medical, food, or precision part line may need a much higher FPY than a rough-cut process.
The useful target is steady improvement against your own baseline, especially on high-scrap lines, changeover-heavy lines, and products with tight quality checks.
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FPY affects the Quality part of OEE because poor first-time quality reduces good output compared with total output. More rejects mean a lower Quality rate in the OEE calculation.
Rework can also hurt Availability and Performance because the line spends time correcting parts instead of making the next order.
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Yes, FPY can be tracked on old machines if you can collect counts and record reject reasons consistently. The machine does not need to be new to show good count, reject count, and total count.
Retrofit hardware and simple operator input make FPY tracking possible without replacing the machine or waiting for end-of-shift paperwork.
