INFICON Presents SmartFDC Machine Learning Anomaly Detection System

The SmartFDC Machine Learning Anomaly Detection System has been released by INFICON, a leading provider of manufacturing software and hardware solutions for the semiconductor and related industries.

SmartFDC uses Machine Learning (ML) to provide easy-to-use tools to equipment and process engineers to minimize product uncertainty and quickly fix production problems while automatically offering Fault Detection and Classification (FDC) coverage. Engineers of all content areas can use the automated and simple-to-understand ML analysis results, which reduces the time it takes to identify inline problems and diagnose excursions detected by the device.

SmartFDC shortens the time it takes to implement fault detection, improves detection capabilities, and gives engineers of all ability levels access to powerful analytical tools. Its machine learning algorithm learns the processes that operate on the equipment without any additional configuration or modification, ensuring that every tool and chamber is tracked as soon as the device is turned on. Engineers are given insight into equipment and processes that improves their ability to recognize and troubleshoot problems as the system fine tunes the learning.

SmartFDC also enhances conventional FDC systems by combining machine learning and engineering expertise into a single intuitive framework that allows factories to quickly scale up deployment and incorporate functionality based on unique requirements without requiring major modifications to current data collection or excursion detection infrastructure, thereby trying to simplify the implementation.