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PCB, MLCC, and solar cells are small, sophisticated electronic components that perform an important role in many products. High-performance quality testing is essential for electronic products, and today, deep learning technology goes beyond the limits of existing inspection automation to quickly detect various atypical defects.

Build a solution for quality inspection with Neurocle's deep learning vision software.

PCB inspection

PCB panel defect inspection
PCB component mounting inspection

Neurocle software detects atypical defects such as short, mouse bite, pin hole. During the PCB fabrication process, the mounting, placement, and number of appropriate components are inspected.


Company 'S' PCB inspection


MLCC inspection

MLCC final surface inspection

Many companies still use conventional methods to inspect MLCCs, causing many overkills and underkills.

Neurocle software recognizes and classifies various defects such as cracks and plating mistakes to minimize inspection error rates.

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Company 'S' MLCC surface inspection


Compact Camera Module (CCM) Inspection

Lens module inspection

The lens module, responsible for the optical part of the CCM, is a key component of a camera.

Neurocle software inspects the bonding quality of the lens assembly process, and detects lens contamination such as scratches or stains.

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Camera Module.png

Company 'L' CCM inspection


Solar Cell Inspection

Panel defect inspection

Solar cell panels come in many different forms, and their defects are quite complex. Most of the solar cell inspection is done through the PL/EL system, where the images are categorized with human eyes.

By learning defective types such as dead cell, broken cell, hotspot, and microcrack, inspection can be automated, and the quality of inspection improved.

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Solar Cell.png

Company 'H' EL inspection

Solar Cell

Innovate product quality inspection with deep learning.

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