• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.35D no.2
• /
• pp.25-32
• /
• 1998

In this paper, we report the result of the three-dimensional topography simultor, 3D-SURFILER(SURface proFILER) for the simulation of topographical evalution of the surface, curing a plasma etching process. We employed cell-removal algorithm to represent the topographical evoluation of the surface. The visibility with shadow effect was developed and applied to the spillover algorithm. To demonstrate the capability of 3D-SURFILER, we compared with simulated profiles with the SEM picture for dry and reactive ion etching(RIE) of the Si$_{3}$N$_{4}$ film and Pt film.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.102-104
• /
• 2006

Auto-Correlated time series (ATS) model was constructed by using the backpropagation neural network. The performance of ATS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 4%. By integrating ATS model into equipment software, process quality can be more stringently monitored while improving device throughput.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.195-200
• /
• 1998

Since the neural network was introduced, significant progress has been made on data handling and learning algorithms. Currently, the most popular learning algorithm in neural network training is feed forward error back-propagation (FFEBP) algorithm. Aside from the success of the FFEBP algorithm, polynomial neural networks (PNN) learning has been proposed as a new learning method. The PNN learning is a self-organizing process designed to determine an appropriate set of Ivakhnenko polynomials that allow the activation of many neurons to achieve a desired state of activation that mimics a given set of sampled patterns. These neurons are interconnected in such a way that the knowledge is stored in Ivakhnenko coefficients. In this paper, the PNN model has been developed using the plasma enhanced chemical vapor deposition (PECVD) experimental data. To characterize the PECVD process using PNN, SiO$_2$films deposited under varying conditions were analyzed using fractional factorial experimental design with three center points. Parameters varied in these experiments included substrate temperature, pressure, RF power, silane flow rate and nitrous oxide flow rate. Approximately five microns of SiO$_2$were deposited on (100) silicon wafers in a Plasma-Therm 700 series PECVD system at 13.56 MHz.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.22 no.4
• /
• pp.680-685
• /
• 2013

In this study, the effect of laser shock peening on a titanium alloy was modeled using different confinements. Both liquid and solid confinement could be applied to laser shock peening, and solid confinement provided a dry laser shock peening process, which has the advantage of a corrosion-free effect. When a different confinement was applied to laser shock peening, a different peening effect would be expected. In our study, the peening effect was numerically modeled and simulated. The main effect of different confinements was a change in the impedances required to confine a shock wave from a plasma. The impedances were assumed with respect to different materials. Johnson-Cook's plastic deformation modeling was applied to the simulation. The strains and residual stresses were calculated to evaluate the confinement effects. When solid confinement was used, the residual stress increased by 60-85%, compared to the case of liquid confinement. However, the depth of the residual stress was slightly deeper. The simulated results could be applied to estimate the peening effect when a different confinement was used in the laser shock peening process.

• Proceedings of the Korean Institute of Surface Engineering Conference
• /
• 2006.10a
• /
• pp.4-5
• /
• 2006

This paper represents modeling and optimization techniques for solar cell process on single-crystalline float zone (FZ) wafers with high efficiency; There were the four significant processes : i)emitter formation by diffusion, anti-reflection-coating (ARC) with silicon nitride using plasma-enhanced chemical vapor deposition (PECVD); iii)screen-printing for front and back metallization; and iv)contact formation by firing. In order to increase the performance of solar cells, the contact formation process is modeled and optimized. This paper utilizes the design of experiments (DOE) in contact formation to reduce process time, fabrication costs. The experiments were designed by using central composite design which is composed of $2^4$ factorial design augmented by 8 axial points with three center points. After contact formation process, the efficiency of the solar cell is modeled using neural networks. This model is used to analyse the characteristics of the process, and to optimize the process condition using genetic algorithms (GA). Finally, find optimal recipe for solar cell efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1244-1247
• /
• 2005

The material removal mechanism of Electrical Discharge Machining (EDM) process has been studied for several decades. However, understanding of the material removal mechanism is still a difficult problem because the mechanism involves complicated physical phenomena including plasma. Especially, for a micro-EDM process, due to the influence of the debris that is generated during the machining process, quantitative modeling of EDM becomes more complex. To understand better the effects of the debris in the micro-EDM process experimentally, a new approach has been introduced in this study. Using a specially designed workpiece holder, the debris generated during the EDM with various process conditions has been collected. Then, using a simulated environment using micro-sized metal powders, the influence of the debris during the single EDM discharge has been observed. The effects of EDM process parameters on the debris size and product quality are discussed.

• Journal of Welding and Joining
• /
• v.14 no.5
• /
• pp.113-121
• /
• 1996

The arc sensor has been most widely used for weld seam tracking through welding current or voltage variation. In this work, the relation between the arc light intensity and welding condition is investigated using heat balance in the Plasma for its possible application to seam tracking in the GMAW process. The arc light intensity is derived to be the function of the arc length and welding current Experiments are carried out to verify the proposed heat balance model. Performances of least square and integration methods to process the signals for seam tracking are compared experimentally. Predicted arc light intensity shows reasonably good agreement with experimental results. The weld seam is successfully tracked through the arc light intensity. The least square and integration methods demonstrate almost same performance of seam tracking with $CO_2$gas shielding.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2005.04a
• /
• pp.55-62
• /
• 2005

In this paper, a CAB/CAE integrated optimal design system is developed, in which design and analysis process is automated using CAD/CAE softwares, for a complicated model for which parametric modeling provided by CAD software is not possible. CAD modeling process is automated by using UG/OPEN API function and UG/Knowledge Fusion provided by Unigraphics. The generated model is transferred to the analysis code ANSYS in parasolid format. Visual DOC software is used for optimization. The system is developed for PLS(Plasma Lighting System), which is a next generation illumination system that is used to illuminate stadium or outdoor advertizing panel. The PLS system consists of more then 20 components, which requires a lot of human efforts in modeling and analysis. The analysis for PLS includes static load, wind load and impact load analysis. As a result of analysis, it is found that the most critical component is a tilt assembly, which links lower & upper body assembly. For more reliable analysis, experiment is conducted using MTS and compared with the Finite element analysis result. The objective in the optimization is to minimize the material volume under allowable stresses. The design variables are three parameters in the tilt assembly that are chosen to be the most sensitive in stress values of twelve parameters. Gradient based method and RSM(Response Surface Method) are used for the algorithm and the results are compared. As a result of optimization, the maximum stress is reduced by 57%.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.3
• /
• pp.105-115
• /
• 2015

In semiconductor etching simulation, The source modeling for generating plasma species is required. In this paper, we modeled the source of plasma etching process with probability distribution and the feature profile with simple geometry objects, then got the flux on the feature profile. The distance between the source and the cell on the modeling parameters of the source, there are a number of particles to be emitted from a source, there is a number (area of the cell) of the cell on the profile with additional parameters to give the calculation of flux. The flux error ratio on both gaussian(Incident Flux) and cosine probability distribution(Incident Neutral Flux) is much decreased as the number of ray is increased but the processing time is more increased than that. The increase of the number of cell and distance makes increase the flux error ratio and the processing time moderately. In view of the processing time through the experimental results in this paper, it is possible to analogize the calculation of appropriate fluxes.

• Journal of The Korean Astronomical Society
• /
• v.46 no.1
• /
• pp.49-63
• /
• 2013

Nonthermal radiation from supernova remnants (SNRs) provides observational evidence and constraints on the diffusive shock acceleration (DSA) hypothesis for the origins of Galactic cosmic rays (CRs). Recently it has been recognized that a variety of plasma wave-particle interactions operate at astrophysical shocks and the detailed outcomes of DSA are governed by their complex and nonlinear interrelationships. Here we calculate the energy spectra of CR protons and electrons accelerated at Type Ia SNRs, using time-dependent, DSA simulations with phenomenological models for magnetic field amplification due to CR streaming instabilities, Alf$\acute{e}$enic drift, and free escape boundary. We show that, if scattering centers drift with the Alf$\acute{e}$en speed in the amplified magnetic fields, the CR energy spectrum is steepened and the acceleration efficiency is significantly reduced at strong CR modified SNR shocks. Even with fast Afv$\acute{e}$nic drift, DSA can still be efficient enough to develop a substantial shock precursor due to CR pressure feedback and convert about 20-30% of the SN explosion energy into CRs. Since the high energy end of the CR proton spectrum is composed of the particles that are injected in the early stages, in order to predict nonthermal emissions, especially in X-ray and ${\gamma}-ray$ bands, it is important to follow the time dependent evolution of the shock dynamics, CR injection process, magnetic field amplification, and particle escape. Thus it is crucial to understand the details of these plasma interactions associated with collisionless shocks in successful modeling of nonlinear DSA.