title: Similarity ratio analysis for early stage fault detection with optical emission spectrometer in plasma etching process.
abstract: A Similarity Ratio Analysis (SRA) method is proposed for early-stage Fault Detection (FD) in plasma etching processes using real-time Optical Emission Spectrometer (OES) data as input. The SRA method can help to realise a highly precise control system by detecting abnormal etch-rate faults in real-time during an etching process. The method processes spectrum scans at successive time points and uses a windowing mechanism over the time series to alleviate problems with timing uncertainties due to process shift from one process run to another. A SRA library is first built to capture features of a healthy etching process. By comparing with the SRA library, a Similarity Ratio (SR) statistic is then calculated for each spectrum scan as the monitored process progresses. A fault detection mechanism, named 3-Warning-1-Alarm (3W1A), takes the SR values as inputs and triggers a system alarm when certain conditions are satisfied. This design reduces the chance of false alarm, and provides a reliable fault reporting service. The SRA method is demonstrated on a real semiconductor manufacturing dataset. The effectiveness of SRA-based fault detection is evaluated using a time-series SR test and also using a post-process SR test. The time-series SR provides an early-stage fault detection service, so less energy and materials will be wasted by faulty processing. The post-process SR provides a fault detection service with higher reliability than the time-series SR, but with fault testing conducted only after each process run completes.
authors.affiliation: Energy and Design Lab, School of Electronic Engineering, Dublin City University, Dublin, Ireland.
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.affiliation: Energy and Design Lab, School of Electronic Engineering, Dublin City University, Dublin, Ireland.
authors.forename: Conor
authors.initials: C
authors.lastname: McArdle
authors.affiliation: Energy and Design Lab, School of Electronic Engineering, Dublin City University, Dublin, Ireland.
authors.forename: Stephen
authors.initials: S
authors.lastname: Daniels
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical
references.citation: Sensors (Basel). 2010;10(6):5703-23
references.pmid: 22219683