Hands-free voice on the line

The problem

The recurring problem is never recognized as recurring.

Critical operational knowledge lives in the line supervisor's head and never enters the system, in an environment where every robotic cell generates dozens of micro-events per shift.

• The line supervisor knows more about the line than any system: which cell has been drifting on one weld point since the last electrode dressing, which fixture clamp needs retouching every two hours, which gun has been tripping its sequence since the last die change upstream.
• Every robotic cell generates dozens of micro-events per shift, and none of them is big enough to open a ticket — which is precisely why they never enter the system.
• Nobody asks the supervisor anything, because they cannot type with a headset and gloves on, and they record nothing, because recording means walking back to the office and opening a screen.
• What survives is a five-minute verbal handover and, at best, a page in a notebook that nobody else reads. The cumulative effect is worse than it looks: the same problem gets solved again every time, by a different person, on a different shift, with no memory of the three previous attempts or of what was already ruled out.

How it fits the IRIS system

Connect in voice mode — iLEAN listens to the supervisor, not to the operators.

Connect voice mode with a custom wake-word. An LLM structures the dictation as an incident linked to the active cell/line/shift, with a voice or push response.

Humans in command, taken literally: it records what the supervisor chooses to dictate, when they choose to. That distinction is not cosmetic — it is what keeps the case alive in month six instead of being read on the floor as a way of tracking people.

See the full IRIS architecture →

Before and after

Today's shift versus the captured shift

Aspect	Today	With iLEAN Connect
Knowledge of the shift	Dies at the end of it	Accumulated, queryable memory
Cell micro-events	Too small to be written down	Recorded in seconds, by voice
Shift handover	Five verbal minutes	An automatic written summary
A recurring cell fault	Invisible: solved again each time	Detected as a pattern with dates
Supervisor's effort	Walk back to the office	Speak while walking the line
Ordinary floor conversation	—	Not recorded

From knowledge that dies at shift end to real-time information cross-referenced with live cell data.

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.

• No standalone payback: this is an enabling piece. The brief frames it as strategic value for continuous improvement, hard to monetize upfront, and that is how it is presented.
• What it does deliver is the raw material of continuous improvement: the cell history that today only exists in one person's head.
• Estimate it with Process Engineering, against how many times this year the same cell fault was diagnosed from scratch.
• And the shift handover goes from five verbal minutes to a written summary that already exists when the next shift walks in.

Strategic value for continuous improvement; hard to monetize upfront. Estimate to validate with Process Engineering.

And the fair question from the production manager

“Is this a way of keeping track of my team?” — no: iLEAN listens to the line supervisor, not to the operators, and only to what they choose to dictate. There is no continuous listening and no location tracking. Structuring a dictation into cell, shift, part number and symptom is an anchored task, where the best models drop below 1.5% error [1], and the supervisor sees the structured record and corrects it if it got something wrong. What they gain is not having to remember, at the end of the shift, what they saw in cell four eight hours earlier.

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