• Transactions on Electrical and Electronic Materials
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• 제13권3호
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• pp.139-143
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• 2012

Optical emission spectroscopy (OES) is often used for real-time analysis of the plasma processes. OES has been suggested as a primary plasma process monitoring tool. It has the advantage of non-invasive in-situ monitoring capability but selecting the proper wavelengths for the analysis of OES data generally relies on empirically established methods. In this paper, we propose a practical method for the selection of OES wavelength peaks for the analysis of plasma etch process and this is done by investigating reactants and by-product gas species that reside in the plasma etch chamber. Wavelength selection criteria are based on the standard deviation and correlation coefficients. Moreover, chemical actinometry is employed for the normalization of the selected wavelengths. We also present the importance of chemical actinometry of OES data for quantitative analysis of plasma. Then, the suggested OES peak selection method is employed.. This method is used to find out the reason behind abnormal etching of PR erosion during a series of $SiO_2$ etch processes using the same recipe. From the experimental verification, we convinced that OES is not only capable for real-time detection of abnormal plasma process but it is also useful for the analysis of suspicious plasma behavior.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2009년도 제38회 동계학술대회 초록집
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• pp.473-473
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• 2010

Plasma is widely used in various commercial etchers and chemical vapor deposition. Unfortunately, real-time plasma process monitoring is still difficult. Some methods of plasma diagnosis is improved, however, it is possible for real-time plasma diagnosis to use non-intrusive probe only. In this research, the object is to investigate the suitability of using impedance analysis and optical emission spectroscopy (OES) for real-time plasma process monitoring. It is assumed that plasma system is a equivalent circuit. Therefore, V-I probe is used for measuring impedance, which can be a new non-intrusive probe for plasma diagnosis. From impedance data, we tried to analyse physical properties of plasma. And OES, the other method of plasma diagnosis, is a typical non-intrusive probe for analyzing chemical properties. The amount of the OES data is typically large, so this poses a difficulty in extracting relevant information. To solve this problem, principal component analysis (PCA) can be used. For fundamental information, Ar plasma and $O_2$ plasma are used in this experiment. This method can be applied to real-time endpoint and fault detections.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.281-283
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• 2005

Processing Plasmas are very sensitive to a variation in process parameters, To maintain process quality and device field, plasma malfunction should be tightly monitored with high sensitivity. A new monitoring method is presented and this was accomplished by applying discrete wavelet transformation to X-ray photoelectron spectroscopy. XPS data were collected during a plasma etching of silicon carbide. Various effects of DWT factor on fault sensitivity were optimized experimentally. Compared to raw data, total percent sensitivity for DWT data demonstrated a significantly improved sensitivity to plasma faults induced by bias power.

• 동굴
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• 제78호
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• pp.29-31
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• 2007

This paper is devoted to a study of the characterization of the plasma state. For the purpose of monitoring plasma condition, we experiment on reactive ion etching (RIE) process. Without actual etch process, generated oxygen plasma, measurement of plasma emission intensity. Changing plasma process parameters, oxygen flow, RF power and chamber pressure have controlled. Using the optical emission spectroscopy (OES), we conform to the unique oxygen wavelength (777nm), the most powerful intensity region of the designated range. Increase of RF power and chamber pressure, emission intensity is increased. oxygen flow is not affect to emission intensity.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2014년도 제46회 동계 정기학술대회 초록집
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• pp.262.2-262.2
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• 2014

Plasma processing is an essential process for pattern etching and thin film deposition in nanoscale semiconductor device fabrication. It is necessary to maintain plasma chamber in steady-state in production. In this study, we determined plasma chamber state with residual gas analysis with self-plasma optical emission spectroscopy. Residual gas monitoring of fluorocarbon plasma etching chamber was performed with self-plasma optical emission spectroscopy (SPOES) and various chemical elements was identified with a SPOES system which is composed of small inductive coupled plasma chamber for glow discharge and optical emission spectroscopy monitoring system for measuring optical emission. This work demonstrates that chamber state can be monitored with SPOES and this technique can potentially help maintenance in production lines.

• 한국레이저가공학회지
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• 제2권1호
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• pp.30-37
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• 1999

Laser-welded Tailored Blank is the hottest thing in many automobile companies. But they demand on weld quality, reproducibility, and formability. So it is the great problem of automation of laser welding process. Therefore, it is requested to construct on-line process monitoring system on high accuracy. The light which is emitted from plasma and spatter in laser welding was detected by photo-diodes. It was found that the light intensity depends on welding speed. laser power, and flow rate of assist gas. The relationship between the plasma and spatter and the weld quality can be used for on-line laser weld monitoring systems.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.474-478
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• 1996

Process monitoring in laser welding is essential for automation and quality control of products. Various signals from laser welding, such as plasma, sound, optical signals, etc., are utilized for monitoring the process and detecting abnormal weld conditions. In this study, both W light from plasma formed above the weld pool and IR signal from the melting pool are detected with photodiodes and PC-based A/D board, and analyzed to give a guidance about the weld quality. Experimental results show the possibility of using the signals for predicting and evaluating the weld qualify and adapting into the system for on-line process monitoring.

• 한국정밀공학회지
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• 제30권1호
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• pp.67-76
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• 2013

We present an innovative real-time laser welding monitoring technique employing the correlation analysis of the plasma plume optical emission generated during the process. The plasma optical radiation emitted during Nd:YAG laser welding of S45C steel samples has detected with a Photodiode and analyzed under different process conditions. The discrete DC voltage difference, filter methods and wavelet transform has been used to decompose the optical signal into various discrete series of sequences over different frequency bands. Considering that wavelet analysis can decompose the optical signals, extract the characteristic information of the signals and define the defects location accurately, it can be used to implement process-control of laser welding.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.27-31
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• 2021

VI probe, which is one of various in-situ plasma monitoring sensor, is frequently used for in-situ process monitoring in mass production environment. In this paper, we correlated the plasma etch results with VI probe data with the small amount of gas flow rate changes to propose usefulness of the VI probe in real-time process monitoring. Several different sized contact holes were employed for the etch experiment, and the etched profiles were measured by scanning electron microscope (SEM). Although the shape of etched hole did not show satisfactory relationship with VI probe data, the chamber status changed along the incremental/decremental modification of the amount of gas flow was successfully observed in terms of impedance monitoring.

• 한국공작기계학회논문집
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• 제17권1호
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• pp.98-105
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• 2008

In this paper, the system for monitoring process of aluminum laser welding was developed using the light signal emitted from the plasma which comes from interaction between material and laser. Photodiode for monitoring system was selected based on the spectrum analysis of light from plasma and keyhole. Behavior of plasma and keyhole was analyzed through the sensor signals. Value of sensor signal represented the light intensity and fluctuation of signal indicated the stability of plasma and keyhole. For the relation between welding condition and sensor signals, the input power and weld geometry greatly effected on the average of each sensor signals. Using the feature values of signals, estimation model for tensile strength of weld was formulated with neural network algorithm. Performance of this model was verified through coefficient of determination and average error rate.