
The cylindrical cells used in EV batteries must be inspected for scratches, dents, contamination or surface discoloration, which can point to structural problems and less reliable or shorter-lived batteries. The inspection setup uses high-resolution cameras to capture the cell surface as it rotates on a conveyor, while multi-angle lighting reveals surface irregularities. Machine vision algorithms analyze the captured images for deviations from the ideal smooth, consistent finish.
Surface defects like pits, scratches and embedded particles can reduce efficiency significantly. Such imperfections can lead to uneven electrochemical reactions during battery and manufacturing cycles, resulting in poor battery performance and reduced lifespan. Zebra's machine vision systems can detect these surface anomalies with high precision, enabling the analysis of surface irregularities to ensure coating uniformity.
Placement of anode and cathode materials must be positioned precisely and consistently to ensure optimal battery performance. Misaligned electrodes, separators, and electrolyte function correctly and safely, impacting the overall reliability of the battery. Our advanced machine vision systems provide precision location of components, ensuring they are positioned correctly within tight tolerances.
Automated inspection and verification of completed EV battery cells are critical for ensuring electrical and mechanical integrity. Zebra's machine vision systems can detect defects such as cracks, delamination, and foreign particles, while surface scans can continuously assess final cell parameters, reducing defective and ensuring compliance with quality standards.
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LOGICOLIS specializes in the storage and distribution of fruits and vegetables. Facing increased demand and the challenge of efficiently managing and dispatching larger volumes of pallets to numerous retail locations, the company implemented Zebra's FS40 fixed industrial scanners fitted to gantries.
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