Final test, confirmed by a human in 2 taps

The problem

The last checkpoint before shipping is still transcribed by hand.

Final test certifies that the unit meets leak-tightness, power draw and temperature specs before moving to packing and shipping to any of more than 50 destination countries — it's the last checkpoint before the unit leaves the plant. Automating its logging without a human looking at it first would risk product certifications.

• Final test certifies that each cooler meets leak tightness, power draw and temperature pull-down before it moves to packing and ships to any of more than 50 destination countries.
• It is the last checkpoint before the unit leaves the plant, and the result is still written on a sheet and typed in at shift end. Leak rate, watts and temperature are copied by hand from the instrument display, often by the same technician who already has the next unit connected.
• Automating that record without a human looking at it first would put product certifications at risk. That is why most plants keep it manual, even knowing it is slow.
• Meanwhile the unit has already been packed and sometimes shipped, with its test result living only on paper. When a question comes back from the field, finding that sheet again takes longer than the test itself.

How it fits the IRIS system

Connect with early human verification — the technician confirms in two taps.

An industrial tablet at the test bench shows a visual summary of what iLEAN just captured from the test — a photo of the measurement device's display, OCR reading. The technician confirms with two taps (confirm / correct). Only then does the data cross over to the central system and the unit's record.

The point is not to remove the technician from the decision; it is to put them at the start of the data instead of the end. The reading is captured, the technician confirms it at the bench, and only then does it reach the unit's record. It is a deliberate choice: data reaches the system faster precisely because a human has seen it first.

See the full IRIS architecture →

Before and after

The final test result on paper versus confirmed at the bench

Aspect	Today	With iLEAN Connect
Leak tightness reading	Written on a sheet	Captured from the instrument display
Power draw and pull-down temperature	Typed in at shift end	Confirmed at the bench
Who validates the data	Nobody, until the transcription	The technician, in two taps
Link to the serial number	Rebuilt afterwards	From the first tap
A correction	Crossed out on paper	Recorded with its author
Data reaching the record unseen	—	Never

Manual transcription of the result at shift end → data validated and traced to the unit in seconds.

Impact estimate

Impact estimate — to be validated with your numbers.

The block below is an estimate to be validated against your plant's actual data. We put it forward so the committee has an order of magnitude; we refine it during the assessment.

• Estimated payback 3-6 months, from full final-test traceability by serial number.
• Manual transcription at shift end becomes data validated and traced to the unit in seconds. No more hunting for test sheets when a field question arrives about a specific serial number.
• The test result exists before the unit is packed, not after it has shipped. Units with a doubtful test can be held before packing instead of recalled from the dock.
• And certifications gain a record with a human confirmation behind every value, which is exactly what an auditor wants to see.

Estimated payback of 3-6 months from full final-test traceability by serial number. Estimate to validate.

And the fair question from the production manager

“And if the OCR misreads the leak rate and the technician taps confirm without looking?” — reading a measurement instrument's display is an anchored task, where the best models drop below 1.5% error [1]. On top of that, each value is checked against the test's pass range: an out-of-range reading cannot be confirmed with one tap, it forces the technician to look and correct.

^[1] OpenAI paper "Why Language Models Hallucinate", 2025 — on the reliability of AI in anchored tasks.