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Real-time fault classification for plasma processes
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Real-time fault classification for plasma processes

Ryan YangRongshun Chen
Sensors, 卷.11(7), 頁碼.7037-7054
07/2011

摘要

Fault classification Optic emission spectrum (OES) Process/equipment fault detection Analytical Chemistry Atomic and Molecular Physics and Optics Biochemistry Instrumentation Electrical and Electronic Engineering
Plasma process tools, which usually cost several millions of US dollars, are often used in the semiconductor fabrication etching process. If the plasma process is halted due to some process fault, the productivity will be reduced and the cost will increase. In order to maximize the product/wafer yield and tool productivity, a timely and effective fault process detection is required in a plasma reactor. The classification of fault events can help the users to quickly identify fault processes, and thus can save downtime of the plasma tool. In this work, optical emission spectroscopy (OES) is employed as the metrology sensor for in-situ process monitoring. Splitting into twelve different match rates by spectrum bands, the matching rate indicator in our previous work (Yang, R.; Chen, R.S. Sensors 2010, 10, 5703-5723) is used to detect the fault process. Based on the match data, a real-time classification of plasma faults is achieved by a novel method, developed in this study. Experiments were conducted to validate the novel fault classification. From the experimental results, we may conclude that the proposed method is feasible inasmuch that the overall accuracy rate of the classification for fault event shifts is 27 out of 28 or about 96.4% in success. © 2011 by the authors; licensee MDPI, Basel, Switzerland.

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