Printed Circuit Board (PCB) Fault Detection

Nowadays many industries heavily depend on devices, those, with printed circuit boards (PCBs) to function properly. However issues like connections, damaged components or short circuits can cause malfunctions that result in downtime and financial losses. It is crucial to identify and resolve thesePCB faults to maintain the operation of electronic systems. On average businesses experience a 23% decrease in productivity due to PCB faults. One of the contributors to this problem is the lack of detection and resolution. To tackle this issue we propose an approach using machine learning techniques for PCB fault detection. Our solution harnesses the power of Web Machine Learning to implement a real time model for detecting PCB faults. By utilizing TensorFlow.js – a JavaScript library for training and deploying machine learning models in web browsers – we can provide instant feedback on the health of PCBs