Title :
Detecting Arcing Events in Semiconductor Manufacturing Equipment
Author :
Subrahmanyam, K. ; Singlevich, Scott ; Ewing, Paul ; Johnson, Mark
Author_Institution :
Adv. Services Eng. Appl. Mater., Inc., Singapore, Singapore
Abstract :
Bi-polar arcs require a high voltage difference between two closely spaced points. As an example, if there is excessive deposition or contamination on the deposition and or cover ring in a physical vapor deposition tool (PVD) tool, a DC bipolar arc can occur leading to ablation of underlying materials, wafer breakage, or chamber damage caused by the discharge. In some cases these incidents are not identified until numerous wafers have been processed. Therefore, it is essential to identify arcing at the time of the event. In this paper, we address arc detection in a PVD chamber. The electrostatic chuck (ESC) critical parameter(s) are captured with 1000 Hz sampling frequency and signal processing techniques such as FFT and wavelet transforms are used to improve the signal-to-noise ratio enhancing the ability to isolate arcs from raw data. This methodology can be implemented on other plasma chamber types.
Keywords :
fast Fourier transforms; fault diagnosis; plasma deposition; production engineering computing; production equipment; semiconductor device manufacture; signal sampling; wavelet transforms; FFT; PVD chamber; ablation; arcing event detection; bipolar arcs; chamber damage; contamination; electrostatic chuck; physical vapor deposition tool; sampling frequency; semiconductor manufacturing equipment; signal processing techniques; wafer breakage; wavelet transforms; Arc discharges; Discrete wavelet transforms; Filtering; Signal processing; Wavelet analysis; Arc detection; arcing; filtering; resampling; semiconductor equipment; signal processing; wavelet;
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
DOI :
10.1109/TSM.2013.2283053