Package Integrity and Sterility

Detect defects, contamination, and label mix-ups

Package, label, and seal integrity are critical to ensure packaging is correct, sterile, and contaminant-free when heading into a doctor’s office or operating room. The cost of product recalls or returns caused by contamination or label mix-ups can be significant. Many medical device manufacturers use ultrasonic sensors or human operators to identify package integrity and sterility issues. But shifts in part size, contrast variations, and random defects that differ in appearance, lead to failing or rejection of good product and passing of potentially dangerous products.

Machine vision systems detect defects and verify package integrity through accurate and repeatable inspection. SolutionBank 3D solutions ensure even and consistent final packaging. Machine vision technology detects safety seal edges and measures the height, width, relative position, and gap size, comparing them to the programmed limits. Tamper seal dimensions which do not comply with programmed limits are rejected, limiting risk of product recalls.

When rule-based vision systems struggle to adjust to seal variations, transparency, or Tyvek, SolutionBank deep learning solutions can be a great addition or alternative. Deep learning reliably identifies foreign objects, void seals, contamination, label, and cosmetic defects that can impact package integrity. With 100% visual inspection, operator errors are eliminated and efficiency is optimized. Deep learning can take this a step further by highlighting the issues in real time, allowing operators or machines to clearly point out the issue and later categorize the problem.


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