Neurealm delivered an AI-powered PCB defect detection solution that automates quality control for printed circuit boards by using computer vision and machine learning to identify manufacturing defects with high accuracy.

Business Context

A leading electronics manufacturer faced challenges with manual PCB inspection, which was time-consuming, inconsistent, and prone to human error. They needed a scalable, automated solution that could detect common and subtle defects (such as missing components, misalignments, solder issues) across high-volume production, reduce inspection costs, and improve overall manufacturing yield.

Solutions

Neurealm developed a customized computer vision and deep learning pipeline to analyze high-resolution PCB images, trained defect-classification models on diverse failure modes, and integrated the AI engine with the client’s inspection workflow. The solution included an intuitive dashboard for review and feedback loops to refine accuracy, edge-optimized inference for real-time performance on the line, and automated reporting to streamline quality traceability across production batches.