Mixed SKU on Textile Pick Face Detection with AI Vision

Five Ways a Clean Pick Face Turns Mixed

Mixed faces are almost never theft or system failure. They come from ordinary handling at speed, where one wrong placement looks fine to the next person who walks past. Apparel and home textiles make it worse, because a style can run to dozens of colour and size variants that sit side by side and look nearly the same once folded. One warehouse guide notes that count mismatches often stem from incorrect putaway or mislabeled cartons rather than true shrinkage. Walk through your own handling points with our DC support team.

What the Camera Reads, and What It Cannot Tell Apart

Here is the honest part. Two polos of the same style and colour that differ only in size look the same when folded or polybagged. No model can reliably tell a folded M from a folded L by shape alone. So iFactory does not try to guess size from appearance. It reads printed identifiers, such as the barcode, size sticker, bag label or hangtag text, and uses colour and pattern only as supporting cues. Every read is then compared with the slotting record in your WMS. See how reads and cues combine in a bin-level walkthrough.

The Per-Bin Read Against the Slotting Master

Each signal carries a different weight. A decoded GTIN is close to proof, because each colour and size variant normally has its own code. Colour is useful for spotting a stranger in the bin, but weak for telling close shades apart. The matrix shows how each signal is used. Weights are tuned to your labelling, so share sample bin photos with our vision support team.

From Mixed Read to Blocked Task in One Pass

The block only helps if it lands before the next picker arrives. Reads are taken after each putaway or replenishment into a bay, and on a fixed schedule for slow faces. A confirmed conflict puts the location on hold through your WMS integration, so open tasks for that bin stop rather than shipping the wrong size. Most WMS platforms offer some form of location hold or lock, and iFactory uses the one yours already has. Plan the hold rules in a WMS integration session.

Four Face States and What Each One Triggers

Vision checks identity, not quantity, so it does not replace the cycle count. What it changes is where counters spend their time. Instead of counting bins on a calendar and hoping to hit the mixed ones, the count list is pointed at faces the camera has flagged. Every adjustment then carries a cause, putaway, returns or breakdown, so the same mistake is fixed upstream. Ask our operations team how this fits your count programme.

What Every Held Location Keeps on File

A hold is only useful later if the record explains it. Each mixed face produces one record that links the image, the reads and the last tasks that touched the bin, so a supervisor can see whether the cause was a replenishment, a returns put-back or a breakdown. Request a sample exception export in a short demo call.

Three Mixed Faces, Three Different Fixes

These are illustrations, not customer cases. They show how the cause found in the record points to a different fix each time, which is the real value of a held bin over a silent mis-pick. Talk through faces like these with our slotting specialists.

Size the Cost of Mixed Faces With Your Own Numbers

We don't quote mis-pick rates, because they vary too much between DCs. Every input below is assumed, and the worksheet does nothing more than multiply them. Put your own count and returns figures in their place, or build it with us in a pick accuracy review.

Catching a face after two picks instead of eight cuts the middle line to a quarter on the same assumptions. Customer goodwill and chargebacks are left out on purpose. Include them only where your records back up a number.

Aisle Cameras, WMS Link and Edge Server, Delivered Ready

iFactory delivers per-bin vision as one package. Cameras are placed to cover your fastest pick faces, and a pre-configured NVIDIA AI server ships racked and ready with the read and compare models loaded, and bin images never leave the building. You rack it, plug in power and Ethernet, and the AI is live. Our deployment team can survey your first aisles.

Built for Textile DCs Where Variants Look Alike

iFactory sits between the aisle and your WMS. It doesn't replace slotting, counting or picking logic. It gives them a check they didn't have. Book a pilot planning call to see where it fits first.

What Textile DC Operations Leads Ask About Mixed Faces