Rita Chattopadhyay
Intel Corporation, USA
Title: Real time monitoring and automatic fault detection in robots in semiconductor fabrication industry
Biography
Biography: Rita Chattopadhyay
Abstract
Losses of wafers and expensive repairs of process equipment are oft en caused due to uncontrolled and unmonitored failures
of components during semiconductor process. High volume manufacturing (HVM) of semiconductor chips employs
large number of robots. Any malfunctioning of these robots causes particle contamination, wafer tip-over, or crash of wafers,
resulting in production yield loss, equipment down time and economic loss. Presently, wafer handling monitoring instruments
diagnose vibrations of a robot at end-eff ector. Detection of anomaly in these vibrations is performed manually during scheduled
maintenance and is highly dependent on the experience of the maintenance personnel. Th is not only is prone to human error,
but also limits large scale deployment in semiconductor fabrications; having thousands of robots in the assembly line. Th e
proposed solution automates this process by monitoring the vibration signal patterns, continuously at real time, to proactively
identify robots that are at the greatest risk of failure. Th e vibration signals are captured from triaxial accelerometers placed near
the bearings in the arms of the robots. Th e proposed method analyzes specifi c parameters of the vibration signal and generates
alerts for maintenance, before the uncontrolled vibrations aff ect production yield. Identifi cation of parameters, which are
indicative of failure, is a great challenge. Th is work presents four such indicative parameters, determined based on exhaustive
time and frequency domain analysis of the vibration data collected from good and faulty robots. Th e proposed method based
on outlier detection methods has been successfully deployed in a semiconductor fabrications using Edge/Cloud architecture
for remote monitoring and alerting.