Allergen Changeover Cleared

The problem

The cleaning is certified. The sign-off is blind.

Moving from a formula with an allergen to one without it requires certified cleaning; today it relies on a human sign-off with no visual evidence, risking cross-contamination of the first batch.

• Moving from a formula with milk, soy, gluten or mustard to one without it requires a certified cleaning of the blender, the loading hopper, the discharge valve and the conveying lines.
• In a dry powder plant much of that cleaning is dry — vacuum, brushes, compressed air — and residue hides in shafts, gaskets and the discharge valve, exactly where nobody looks under time pressure.
• Today the release relies on a signature on a checklist, with no visual evidence of the state of each point at the moment of signing. The person signing is often the same person who cleaned, under pressure to restart.
• If residue remains, the first batch of the allergen-free formula is cross-contaminated, and that batch carries your customer's 'free-from', kosher or halal claim.

How it fits the IRIS system

Edge with JIDOKA AI — the line does not start until every critical point is clear.

Edge + JIDOKA AI: fixed cameras at every critical point compare the current state against the reference 'clean' state; the line doesn't start until all clear and quality signs off with visual evidence.

The cameras do not replace the cleaning team or quality's sign-off. They change what the sign-off rests on: each critical point compared with its reference clean state, and the release signed on that evidence instead of on memory and good faith. When an auditor or a customer asks how you know the blender was clean, the answer is an image per point, not a recollection.

See the full IRIS architecture →

Before and after

Allergen changeover today versus changeover cleared by camera

Aspect	Today	With iLEAN Edge
What the blender release rests on	A checklist signature	Images of every critical point
Residue in blender shafts and gaskets	Found by a swab, if taken there	Compared with the clean reference
Discharge valve and loading hopper	Checked by eye	Checked by fixed camera
Start-up before allergen clearance	Possible under pressure	Blocked by JIDOKA AI
Changeover evidence for the certifier	A signed sheet	Timestamped images per point
First allergen-free batch after the clean	Under suspicion	Released on evidence

Blind sign-off with contamination risk → sign-off backed by visual evidence per critical point.

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.

• We do not fix a payback range for this case, because it depends on how much of your volume runs on allergen-sensitive lines; with your product mix it can be estimated and validated.
• What it protects is the 'free-from', kosher and halal certification that your customers buy from you, and that a single cross-contaminated batch can put on the table.
• The blind sign-off becomes a sign-off backed by visual evidence for each critical point of the blender and its discharge.
• And the evidence is captured automatically at every changeover, which is the raw material of the audit evidence pack in the next case.

Protects 'free-from'/kosher/halal certification · payback depends on sensitive-line share — estimate to validate

And the fair question from the production manager

"What if the camera blocks the restart over a speck of dust?" — it is the right objection, because changeover time is production time. Comparing a point with its own reference image is an anchored task, where the best models drop below 1.5% error [1], and the system does not block silently on doubt: it shows the image to quality, who decides. It stops on a verifiable difference, not on model uncertainty.

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