Cryovac, Inc.

Kalpit Shailesh Mehta

Solomon Bekele

Richard Keith Watson

Honglei Li

Dewitt Jones

Gregory E McDonald

James Mize

Siddarth Sreeram

Benjamin Scott Oslund

Kevin Heitz

Wafic Omar El-Kara

Elyse Ford

Marshall Hewitt

A process for monitoring seal quality of a packaging article. In one embodiment, the process for monitoring the seal quality includes sealing a film to form packaging article and forming a seal area. The seal area is analyzed by a vision system to acquire image data of the seal area. A vision inspection engine analyzes the image date to determine the continuity of the seal, the strength of the seal, or both.

System for in-line inspection of seal integrity

A process, product, and system for detecting a defective vacuum in a packaged product. The process may include providing a packaged product including a product enclosed within a packaging article. The packaging article may include a film having at least one layer containing a fluorescence-based indicator. The process may further include exposing the packaged product to incident electromagnetic energy to produce an excited fluorescence-based indicator, such that the excited fluorescence-based indicator emits fluorescent electromagnetic energy; and determining, based on the fluorescent electromagnetic energy emitted by the excited fluorescence-based indicator, that gas is present within the packaging article.

Inspection of vacuum packaged product for detection of gas inside package

Vacuum seal packages can be classified based on image data. Training image data is received that includes image data about first vacuum seal packages. Labels associated with the first vacuum seal packages are received, where each of the labels includes a state of one of the first vacuum seal packages. A trained classification model is developed based on the training image data and the received labels. Image data representative of a second vacuum seal package is received. The image data is inputted into the trained classification model, where the trained classification model is configured to classify a state of the second vacuum seal package based on the image data. The state of the second vacuum seal package is received from the trained classification model.

Image-data-based classification of vacuum seal packages

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Charlotte, NC, United States of America

Kalpit Shailesh Mehta