Tracking plasma etch process variations using principal component analysis of oes data
نویسندگان
چکیده
This paper explores the application of principal component analysis (PCA) to the monitoring of within-lot and between-lot plasma variations that occur in a plasma etching chamber used in semiconductor manufacturing, as observed through Optical Emission Spectroscopy (OES) analysis of the chamber exhaust. Using PCA, patterns that are difficult to identify in the 2048-dimension OES data are condensed into a small number of principle components (PCs). It is shown, with the aid of experimental data, that by simply tracking changes in the directions of these PCs both inter-lot and intra-lot patterns can be identified.
منابع مشابه
Low-Open Area Endpoint Detection using a PCA based T Statistic and Q Statistic on Optical Emission Spectroscopy Measurements
This paper will examine an approach for automatically identifying endpoint (the completion in etch of a thin film) during plasma etching of low open area wafers. Since many endpointing techniques use a few manually selected wavelengths or simply time the etch, the resulting endpoint detection determination may only be valid for a very short number of runs before process drift and noise render t...
متن کاملEndpoint in plasma etch process using new modified w-multivariate charts and windowed regression
Endpoint detection is very important undertaking on the side of getting a good understanding and figuring out if a plasma etching process is done in the right way, especially if the etched area is very small (0.1%). It truly is a crucial part of supplying repeatable effects in every single wafer. When the film being etched has been completely cleared, the endpoint is reached. To ensure the desi...
متن کاملLinear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES
The combinations of inductively coupled plasma-optical emission spectrometry (ICP-OES) and three classification algorithms, i.e., partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM) and soft independent modeling of class analogies (SIMCA), for discriminating different brands of Iranian bottled mineral waters, were explored. ICP-OES was used for th...
متن کاملStudy of Physical and Chemical Soil Properties Variations Using Principal Component Analysis Method in the Forest, North of Iran
The field study was conducted in one district of Educational-Experimental forest at Tehran University (Kheirood-Kenar forest) in the North of Iran. Eighty-five soil profiles were dug in the site of study and several chemical and physical soil properties were considered. These factors included: soil pH, soil texture, bulk density, organic carbon, total nitrogen, extractable phosphorus and depth ...
متن کاملMultivariate Endpoint Detection of Plasma Etching Processes
In plasma etching processes it is critical to know when the film being etched has cleared to the underlying film, i.e. to detect endpoint, in order to achieve the desired device performance in the resulting integrated circuit. The most highly utilized sensor technology for determining endpoint has historically been optical emission spectroscopy (OES), because it is both non-invasive and highly ...
متن کامل