• Title/Summary/Keyword: Plasma modeling

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Heat source modeling of laser arc hybrid welding considering keyhole formation (키홀 형성을 고려한 레이저 아크 하이브리드 용접 열원 모델링)

  • Jo, Yeong-Tae;Na, Seok-Ju
    • Proceedings of the KWS Conference
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    • 2005.06a
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    • pp.97-99
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    • 2005
  • Laser arc hybrid process is actively researched as a new welding method since it has several advantages by the combination of laser beam and electric arc. By the coupling of two different heat sources, laser and arc mutually assist and influence. High power laser can make the deep keyhole and arc plasma can form the large bead shape. In this paper the effect of two different heat sources to weld bead are investigated and as a result of analysis, it is shown that the lower part of keyhole is heated by laser and the upper part of weld pool is dominantly heated by arc.

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Neural Network Modeling of Actinometric Optical Emission Spectroscopy Information for Mo nitoring Plasma Process (플라즈마 공정 감시를 위한 Actinometric 광방사분광기 정보의 신경망 모델링)

  • Kwon, Sang-Hee;Bo, Kwang;Lee, Kyu-Sang;Uh, Hyung-Soo;Kim, Byung-Whan
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.177-178
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    • 2007
  • 플라즈마 공정은 집적회로 제작을 위한 미세 박막의 증착과 패턴닝에 핵심적으로 이용되고 있다. 본 연구에서는 플라즈마공정감시와 제어에 응용될 수 있는 모델을 제안한다. 본 모델은 광방사분광기 (Optical emission spectroscopy-OES)정보와 역전파 신경망을 이용해서 개발하였다. 제안된 기법은 Oxide 식각공정에서 수집한 데이터에 적용하였으며, 체계적인 모델링을 위해 공정데이터는 통계적 실험계획법을 적용하여 수집되었다. Raw OES 정보대신, Actinometric OES 정보를 이용하였으며, 신경망의 예측성능은 유전자 알고리즘을 이용해서 증진시켰다. OES의 차수를 줄이기 위해 주인자 분석 (Principal Component Analysis-PCA)을 세 종류의 분산(100, 99, 98%)에 대해서 적용하였다. 최적화한 모델의 예측에러는 323 $\AA/min$이었다. 이전에 PCA를 적용하고 은닉층 뉴런의 함수로 최적화한 모델의 예측에러는 570 $\AA/min$이었으며, 개발된 모델은 이에 비해 43% 증진된 예측 성능을 보이고 있다.

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Modeling of Plasma Etch Non-Uniformity by Using OES Information and Neural Network (OES 정보와 신경망을 이용한 플라즈마 식각들 비균일도의 모델링)

  • Kwon, Min-Ji;Kim, Byung-Whan
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.403-404
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    • 2007
  • 소자 수율을 향상시키기 위해서는 웨이퍼 전체에 걸쳐 플라즈마 공정특성이 균일하게 분포되어야 한다. 본 연구에서는 Actinomeric 광 반사분광기 (Otical Emission Spectroscopy) 정보를 이용하여 식각률 비균일도에 대한 모델을 개발하였다. 제안된 기법은 Oxide 식각공정에서 수집한 데이터에 적용하였으며, 체계적인 모델링을 위해 공정데이터는 통계적 실험계획 법을 적용하여 수집되었다. 신경망의 예측성능은 유전자 알고리즘을 이용해서 증진시켰다. OES의 차수를 줄이기 위해 주인자 분석을 세 종류의 분산(100, 99, 98%)에 대해서 적용하였다. 개발된 모델은 발표된 이전의 모델에 비해 17% 증진된 예측성능을 보였다.

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Neuron gradient control by random generator and application to modeling a plasma etch process data (난수발생기를 이용한 뉴런경사 제어와 플라즈마 식각공정 데이터 모델링에의 응용)

  • Kim, Sung-Mo;Kim, Byung-Whan
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2582-2584
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    • 2003
  • 역전파 신경망 (BPNN)은 반도체 공정 모델링에 효과적으로 응용되고 있다. 뉴런의 활성화 함수는 동일한 값을 가지며, 이로 인해 예측정확도를 증진하는 데에는 한계가 있었다. 본 연구에서는 난수발생기(Random generator-RG)를 이용하여 뉴런 경사들이 다중값을 가지도록 최적화하였다. 본 기법은 은닉충의 뉴런수의 함수로 고찰하였으며, 종래의 고정된 경사를 갖는 모델과 그 성능을 비교 평가하였다. 평가에 이용된 데이터는 플라즈마 식각 공정데이터이며, 모델에 이용된 응답은 식각률과 프로파일 각이다. 비교결과 종래의 모델에 비해 예측정확도가, 식각률의 경우 19%-43%, 프로파일의 경우 10%-56% 정도 향상하였으며, 이는 제안된 기법이 모델개발에 매우 효과적으로 적용될 수 있음을 보여준다.

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Predictive Neural Network Modeling for the Characterization of $SiO_2$ Film Deposited Using PECVD (PECVD로 증착된 실리콘 산화막의 특성분석을 위한 신경망 모델링)

  • Kim, Hee-Youn;Park, In-Hye;Hong, Sang-Jeen
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2006.06a
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    • pp.186-187
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    • 2006
  • 본 논문에서는 PECVD를 이용하여 증착시킨 실리콘 산화막에 영향을 주는 파라미터 입력에 따른 박막의 특성을 평가하기 위하여 먼저 통계적 실험계획을 통해 산화막 특성에 유의한 영향을 미치는 요인을 분석하고, 분석된 결과를 이용하여 가장 유의한 교호작용을 신경망 모델링에서 입력파라미터로 포함시킴으로서 교호작용을 고려하지 않은 경우와의 학습결과를 비교하여 두가지 모델링 방법 중 교호작용을 고려한 신경망 모델의 경우가 PECVD의 물리적 현상을 더 명확히 설명할 수 있음을 확인했다.

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On-line control of product uniformity for quality improvement (품질향상을 위한 제품 균일성의 On-Line 제어)

  • Ha, Sungdo
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.3
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    • pp.70-79
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    • 1996
  • In off-line process optimization, process parameters are controlled such that the process is robust against changes in equipment conditions and incoming materials. The off-line methods, however, are not effective when the changes are so large that process parameters need to be adjusted. On-line control can respond to such large changes, but process uniformity has not been controlled on-line due to the difficulties in modeling. This paper is aimed at developing a new on-line control methodology where the uniformity is controlled effectively. The process variability is categorized based on the physical considerations, and the process parameters are classi- fied considering their effects on the categorized process variabilities. On-line control is performed with the properly selected process parameters so that robustness may not be degraded. The developed methodology is applied to the single wafer plasma etching processes, which resulted in both higher within-a-wafer uniformity and compens- ation of the incoming material non-uniformity.

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Simple modeling to explore temperatures, heated temperature, and Kappa values of a current sheet observation

  • Lee, Jin-Yi;Raymond, John C.;Reeves, Katharine K.;Shen, Chengcai;Kahler, Stephen;Moon, Yong-Jae;Kim, Yeon-Han
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.2
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    • pp.79.2-79.2
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    • 2021
  • We explore the range of possibilities of temperatures, heated temperature, and Kappa values of a current sheet observation on 2017 September 10. First, we construct a grid model with rapid heating (Theat) and various Kappa (κ) values. We assume a simple density model and use adiabatic cooling to set the temperature during expansion. Next, we calculate the ion fractions using a time-dependent ionization model with adiabatic cooling and various Kappa values. The calculated ion fractions are used to simulate the DNs of the Atmospheric Imaging Assembly on board the Solar Dynamic Observatory. Then, we explore the possible range of the temperatures and Kappa values, comparing the simulated images with the observations. Finally, we discuss the range of the heated temperature and Kappa values and whether the result of this study suggests continuous heating of the current sheet plasma during the expansion.

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Neural Network-based Time Series Modeling of Optical Emission Spectroscopy Data for Fault Prediction in Reactive Ion Etching

  • Sang Jeen Hong
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.4
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    • pp.131-135
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    • 2023
  • Neural network-based time series models called time series neural networks (TSNNs) are trained by the error backpropagation algorithm and used to predict process shifts of parameters such as gas flow, RF power, and chamber pressure in reactive ion etching (RIE). The training data consists of process conditions, as well as principal components (PCs) of optical emission spectroscopy (OES) data collected in-situ. Data are generated during the etching of benzocyclobutene (BCB) in a SF6/O2 plasma. Combinations of baseline and faulty responses for each process parameter are simulated, and a moving average of TSNN predictions successfully identifies process shifts in the recipe parameters for various degrees of faults.

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Prediction of the human in vivo antiplatelet effect of S- and R-indobufen using population pharmacodynamic modeling and simulation based on in vitro platelet aggregation test

  • Noh, Yook-Hwan;Han, Sungpil;Choe, Sangmin;Jung, Jin-Ah;Jung, Jin-Ah;Hwang, Ae-Kyung;Lim, Hyeong-Seok
    • Translational and Clinical Pharmacology
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    • v.26 no.4
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    • pp.160-165
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    • 2018
  • Indobufen ($Ibustrin^{(R)}$), a reversible inhibitor of platelet aggregation, exists in two enantiomeric forms in 1:1 ratio. Here, we characterized the anti-platelet effect of S- and R-indobufen using response surface modeling using $NONMEM^{(R)}$ and predicted the therapeutic doses exerting the maximal efficacy of each enantioselective S- and R-indobufen formulation. S- and R-indobufen were added individually or together to 24 plasma samples from drug-naïve healthy subjects, generating 892 samples containing randomly selected concentrations of the drugs of 0-128 mg/L. Collagen-induced platelet aggregation in platelet-rich plasma was determined using a Chrono-log Lumi-Aggregometer. Inhibitory sigmoid $I_{max}$ model adequately described the anti-platelet effect. The S-form was more potent, whereas the R-form showed less inter-individual variation. No significant interaction was observed between the two enantiomers. The anti-platelet effect of multiple treatments with 200 mg indobufen twice daily doses was predicted in the simulation study, and the effect of S- or R-indobufen alone at various doses was predicted to define optimal dosing regimen for each enantiomer. Simulation study predicted that 200 mg twice daily administration of S-indobufen alone will produce more treatment effect than S-and R-mixture formulation. S-indobufen produced treatment effect at lower concentration than R-indobufen. However, inter-individual variation of the pharmacodynamic response was smaller in R-indobufen. The present study suggests the optimal doses of R-and S-enantioselective indobufen formulations in terms of treatment efficacy for patients with thromboembolic problems. The proposed methodology in this study can be applied to the develop novel enantio-selective drugs more efficiently.

A Study of the Structure and Luminescence Properly of BaMgAl10O17:Eu2+ Blue Phosphor using Scattering Method (Scattering법을 이용한 BaMgAl10O17:Eu2+ 청색형광체의 구조와 발광특성 연구)

  • 김광복;김용일;구경완;천희곤;조동율
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.15 no.1
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    • pp.67-74
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    • 2002
  • A phosphor for Plasma Display Panel, BaMgAl$_{10}$ O$_{17}$ :Eu$^{2+}$, showing a blue emission band at about 450nm was prepared by a solid-state reaction using BaCO$_3$, $Al_2$O$_3$, MgO, Eu$_2$O$_3$ as starting materials wish flux AlF$_3$. The study of the behaviour of Eu in BAM phosphor was carried out by the photoluminescence spectra and the Rietveld method with X-ray and neutron powder diffraction data to refine the structural parameters such as lattice constants, the valence state of Eu, the preferential site of Mg atom and the site fraction of each atom. The phenomenon of the concentration quenching was abound 2.25~2.3wt% of Eu due to a decrease in the critical distance for energy transfer of inter-atomic Eu. Through the combined Rietveld refinement, R-factor, R$_{wp}$, was 8.11%, and the occupancy of Eu and Mg was 0.0882 and 0.526 at critical concentration. The critical distance of Eu$^{2+}$ in BAM was 18.8$\AA$ at 2.25% Eu of the concentration quenching. Furthermore, c/a ratio was decreased to 3.0wt% and no more change was observed over that concentration. The maximum entropy electron density was found that the modeling of $\beta$-alumina structure in BaMgAl$_{10}$ O$_{17}$ :Eu$^{2+}$correct coincided showing Ba, Eu, O atoms of z= 1/4 mirror plane.e.ane.e.