CASE STUDY

PCB Wafer Semiconductor boards

Due to the inherent fragility of PCB Wafer Semiconductor boards, along with their intricate complexity, accentuates their vulnerability to defects, thereby emphasizing the urgent requirement for this global semiconductor supply to have a robut in-house defect detection solution.

The solution required must have the capability to identify defects at a sub-micrometer scale, significantly exceeding the confines of human visual inspection.

Due to this requirement, Mindtrace was selected to create a bespoke AI defect detection solution.

Challenges

Outcome

Mindtrace successfully engineered a tailor-made AI solution, harnessing the power of the Brain-Sense™ Platform, to detect defects at a sub-micrometer scale, boasting an unparalleled industry-leading accuracy rate of 96%.

What sets this solution apart is not only its remarkable accuracy but also its remarkable ability to identify defects that were absent from the initial training dataset, showcasing its exceptional adaptability and robustness.

AI Brains Used

1
Detection

Identifies defect types, severity & location.

1
Classification

Object identification & classification.

1
Analytics

Generates insights & recommendations.

70

Learning Samples

96

Defects Detected

5

Delivery Time

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