Are You Solving the Wrong Inspection Problem?

Investing in systems to check for simple issues, like label presence, is common in logistics and packaging. However, if you're losing thousands weekly to line jams and high return rates, you're tackling the wrong problem.

The issue isn't basic labeling; it's structural integrity and the subtle, unpredictable flaws older systems can’t see.

Traditional, rule-based inspection is completely blind to the problems that truly sink your bottom line:

Physical Distortion: Boxes with subtle bulges, slight tears, or crushed corners often get waved through, only to cause catastrophic jams or be rejected by a customer upon arrival.
Random Variation: In high-mix fulfillment, defects are too random and variable for fixed logic to catch, leading to high false-reject rates or, worse, missed failures.
Zero Diagnostics: If your system just flags "FAIL," it gives you no data on the defect location or type, leaving the root cause in the folder or sealer uncorrected.

Keep an eye on this space if you are looking to move beyond solving symptoms and guarantee package quality!

The issue isn't basic labeling; it's structural integrity and the subtle, unpredictable flaws older systems can’t see.

Traditional, rule-based inspection is completely blind to the problems that truly sink your bottom line:

Physical Distortion: Boxes with subtle bulges, slight tears, or crushed corners often get waved through, only to cause catastrophic jams or be rejected by a customer upon arrival.
Random Variation: In high-mix fulfillment, defects are too random and variable for fixed logic to catch, leading to high false-reject rates or, worse, missed failures.
Zero Diagnostics: If your system just flags "FAIL," it gives you no data on the defect location or type, leaving the root cause in the folder or sealer uncorrected.

Keep an eye on this space if you are looking to move beyond solving symptoms and guarantee package quality!

In Other News- Robotic Bin Picking System at Penna Flame Picks Large, Heavy Industrial Parts

With assistance from CapSen Robotics, Penna Flame Industries integrated advanced 3D vision and machine learning algorithms with a FANUC robot to automate the handling and packing of large steel components.

Vision Systems Design- a global media source serving engineers and engineering managers at OEMs, system integrators, and end-user organizations- recently published a detailed article about this application. Click the button to read the full feature.