Clear meat tray on a roller conveyor outlined in yellow and labeled Seal Defect Detected

Use cases

How do meat processors detect tray seal defects after sealing?

A short-wavelength infrared (SWIR) camera after the sealer sees through the film and checks the seal on every tray in real time. Video-to-Action AI flags weak, incomplete or compromised seals, saves an image and video of each one, and can trigger the line's reject system before the tray is cased.

Meat Processing

Quality Assurance

What it catches

After sealing, Video-to-Action AI checks the seal on every tray for:

Weak seals that may fail later in the cold chain
Incomplete seals along an edge
Compromised seals, such as a break in the seal line
Seal defects down to about 3 mm

Why manual checks miss it

A bad seal on a clear tray is easy to miss at line speed, and sampling checks only a few packs per run. A failed seal shortens shelf life and can lead to leaks, complaints or a recall long after the tray left the plant. By then, finding which sealer and which run caused it is hard.

How it acts

VITA, Maneva's quality and downtime agent, checks the seal on every tray in real time. When it finds a weak, incomplete or compromised seal, it captures an image and video, and can send the signal to the line's reject system so the tray is removed before it is cased.

The images become a diagnostic tool. Because every bad seal is recorded by time and line, a run of failures points to the cause, such as sealer temperature, film alignment or product placement, so the team can fix it before more trays are affected.

Where it sits on the line

The camera sits directly after the sealer, looking down at the trays as they leave the machine. A standard camera only sees the surface of the film; checking the seal itself takes a short-wavelength infrared (SWIR) camera that sees through plastic. It can cover one or more lines. Maneva helps choose the camera and where it goes.

Result

Every tray is checked instead of a sample, and seal failures are caught in the plant instead of at the customer. Brenda Salinas explains what that is worth in practice. Read the article.

See it on a line like yours →

More quality checks for packed product: AI for quality assurance →

Frequently Asked Questions

Didn't find what you need? Our team will walk you through Video-to-Action AI and show how it fits your production environment.

Can a camera see a seal through clear film?

Yes, with the right camera. A short-wavelength infrared (SWIR) camera sees through plastic film and checks the seal itself. A standard camera only sees the surface of the film.

What happens to a tray with a bad seal?

It is rejected or rerouted for repacking before it reaches the case, and logged with its image, so the team can trace which sealer and which shift it came from.

Do we need new cameras?

It depends on your site and the problem you want to solve. Some customers can start with the cameras they already have. Many need at least one new off-the-shelf camera placed and set up for the task, so the AI sees exactly what it needs to see.

Maneva helps you scope this from the start. We look at your line, the result you want, and what the camera needs to capture, then recommend the right camera and where to put it.

Maneva is hardware agnostic and connects to a wide range of camera types, including:

Standard RGB and security cameras for many quality, downtime, safety and efficiency use cases
3D and depth cameras for measuring volume, position and dimensions
Thermal and infrared cameras for heat signatures and low-light areas
Short-wavelength infrared (SWIR) cameras, which see through plastic to check seal integrity
High-resolution precision cameras for defects under a millimeter across large surfaces

If you can see it in the video, our AI can understand it and act on it. Start with one line, and we'll help you choose the setup that gets you there.