Catch bad packs before the case packer.

Fill, seal, cap, count, placement and damage, checked on every pack, with a reject timed to the pack and confirmed when it fires.

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Problems

What this station catches.

Fill level

Packs and bottles under- or over-filled. See Food and Beverage.

Label placement (360°)

Missing, skewed or wrinkled labels. See Beverage.

Containers

Cracked or dirty empties. See Beverage.

Product appearance

Shape, color, breakage, bloom, and enrobing. See Food.

How it works

How the station checks.

A timed, confirmed reject

The reject is timed to the part and confirmed when it fires.

A record of every reject

Every reject logged with image and lot. See Traceability.

Pass or fail

From picture to reject.

01

Capture

A photo eye or encoder triggers the camera, and a short strobe freezes the moving pack. Filters even out brightness and noise when the check needs it.

02

Locate

The software finds the pack, so the checks land in the right place on a pack that arrives turned or off center.

03

Measure

Pixels become numbers: fill height, piece count, seal width, the size of a mark.

04

Decide

Each number is compared with limits set from real good and bad samples. A fail fires the reject when that unit reaches it, and the image and reason are saved.

05

Rules or deep learning

Rule-based tools suit measurements, counts, and presence, and each reject traces to a limit. Deep learning suits faults that vary in look, such as cosmetic marks and wrinkles, and trains on many labeled pictures. Many stations use both. See How machine vision works.

Handed over at site acceptance.

  • Functional specification
  • Electrical drawings and I/O list
  • Commented PLC and vision program
  • Site acceptance test
  • Operator and maintenance training
  • IQ/OQ/PQ support documents

Tell us what keeps going wrong.

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