Catching the defect at line speed, not in the sample

Quality control by sampling tells you about the sample. On a line running at up to 400 batteries a second, a defect pattern can run a long time before a sampled check finds it, and by then the cost is measured in pallets rather than cells.

Manual inspection could not keep pace with the line without either slowing it down or letting defects through.

We put a high-speed camera and computer vision on the line itself, classifying every battery as it passed into good, leaking or scratched, with the model trained through a data-collection and investigation process on the real defects the line produces.

When the system flags a leaking or scratched cell, a precision jet of air redirects it into a recycle bin so only good batteries carry on. Operators get real-time feedback, so a process drifting shows up in seconds rather than at the next audit.

Inspection moved from a periodic check to a continuous one, covering every unit instead of a sample, and defective cells are sorted for recycling rather than reaching a customer. The loop between a process drifting and someone knowing about it shortened from hours to seconds.

The output was built for the operator on the line, not a data-science report, and the data it gathers doubles as a source of insight for continuous improvement.