• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.464-464
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• 2008

This study investigated the slow cooling conditions in the molding of aspheric glass lens using the design of experiment (DOE). The optimization of the slow cooling conditions with respect to the form accuracy (PV) of the molded lens were ascertained by employing full factorial design. As a result of the analysis of variance (ANOVA) and P-value (significance level), it was verified that slow cooling rate represent the most significant operative variables that affect the corresponding response variable. In the optimum condition, the molded lens show 82% of transcription ratio.

• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.120-124
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• 2002

A new methodology is presented to diagnose faults in equipment plasma. This is accomplished by using neural networks as a pattern recognizer of radio frequency (rf) impedance match data. Using a match monitor system, the match data were collected. The monitor system consisted mainly of a multifunction board and a signal flow diagram coded by Visual Designer. Plasma anomaly was effectively represented by electrical match positions. Twenty sets of fault-symptom patterns were experimentally simulated with variations in process factors, which include rf source power, pressure, Ar, and $O_$2 flow rates. As an input to neural networks, two means and standard deviations of positions were used as well as a reflected power. Diagnostic accuracy was measured as a function of training factors, which include the number of hidden neurons, the magnitude of initial weights, and two gradients of neuron activation functions. The accuracy was the most sensitive to the number of hidden neurons. Interaction effects on the accuracy were also examined by performing a 2$^$4 full factorial experiment. The experiments were performed on multipole inductively coupled plasma equipment.

• Journal of computational fluids engineering
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• v.14 no.4
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• pp.31-40
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• 2009

Although optimization by sequentially refining metamodels is known to be computationally very efficient, the metamodel that can be used for this purpose is limited to Kriging method due to the difficulties related with sample points selections. The present study suggests a novel method for sequentially refining metamodels using Pareto Frontiers, which can be used independent of the type of metamodels. It is shown from the examples that the present method yields more accurate metamodels compared with full-factorial optimization and also guarantees global optimum irrespective of the initial conditions. Finally, in order to prove the generality of the present method, it is applied to a 2D transonic airfoil optimization problem, and the successful design results are obtained.

• International Journal of Fluid Machinery and Systems
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• v.9 no.4
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• pp.313-324
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• 2016

Surrogate model based shape optimization methodology to enhance performance of a centrifugal pump has been implemented in this work. Design variables, such as blade number and blade angles defining the pump impeller blade shape were selected and a three-level full factorial design approach was used for efficiency enhancement. A three-dimensional simulation using Reynolds-averaged Navier Stokes (RANS) equations for the performance analysis was carried out after designing the geometries of the impellers at the design points. Standard $k-{\varepsilon}$ turbulence model was used for steady incompressible flow simulations. The optimized impeller incurred lower losses by shifting the trailing edge towards the impeller pressure side. It is observed that the surrogates are problem dependent and most accurate surrogate does not deliver the best design always.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.462-463
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• 2007

신경망을 이용하여 반구형 유도결합형 플라즈마 장비에 대한 전자밀도의 예측모델을 개발하였다. 신경망으로는 Radial Basis function Network를 이용하였고, 신경망의 예측성능은 유전자 알고리즘을 이용하여 최적화하였다. 체계적인 모델링을 위해 $2^4$ 전 인자 (Full Factorial) 실험계획법을 이용하였다. 개발된 모델을 이용하여 공정변수에 따른 전자밀도의 영향을 고찰하였다. 전자밀도는 팁 위치(즉 챔버 높이)에 가장 많은 영향을 받았으며, 소스전력과 압력의 변화에 따른 전자밀도의 변화는 작았다. 팁 위치는 소스전력 변화에 영향을 받지 않았지만, 압력변화는 팁 위치에 따라 복잡하게 전자밀도에 영향을 미쳤다.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.6
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• pp.126-133
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• 2008

Linear motors are efficient mechanism that offers high speed and positioning accuracy. By eliminating mechanical transmission mechanisms such as ball screw or rack-pinion, much higher speed and greater acceleration can be achieved without backlash or excessive friction. However, an important disadvantage of linear motor system is its high power loss and heating up of motor and neighboring machine components on operation. For the application of the linear motors to precision machine tools an effective cooling method and thermal optimizing measures are required. This paper presents an investigation into the thermal behavior of linear motors with the objective of deriving the optimum cooling conditions. To reach these goals several experiments were carried out, varying operating and cooling conditions. From the experimental results, this research proposed cooling conditions to improve the thermal characteristics of the linear motors.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2007.04a
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• pp.165-166
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• 2007

신경망을 이용하여 반구형 유도결합형 플라즈마 장비에 대한 전자온도의 예측모델을 개발하였다. 신경망으로는 Radial Basis Function Network을 이용하였고, 신경망의 예측성능은 유전자 알고리즘을 이용하여 최적화하였다. 체계적인 모델링을 위해 $2^4$ 전 인자 (Full Factorial) 실험획법을 이용하여 $Cl_2$ 플라즈마에서의 데이터를 수집하였다. 최적화된 전자온도 모델의 예측성능은 0.143 eV이었다. 개발된 모델을 이용하여 공정변수에 따른 예측온도의 영향을 고찰하였다. 소스전력과 압력의 변화에 따른 전자온도의 변화는 작았다. 그러나 $Cl_2$ 유량과 특히 척위치의 증가에 따른 전자온도의 증가는 현저하였으며, 이는 고이온밀도의 형성에 기인하는 것으로 해석되었다.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.5
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• pp.61-66
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• 2022

This study investigated the characteristics and relationship between surface roughness and vibration according to the cutting conditions in the slot milling of AL7075-T6. The spindle speed, feed, and depth of cut were selected as independent variables and the amplitude of acceleration and surface roughness as dependent variables. Feed affected the surface roughness. As the spindle speed increased, the amplitude of vibration increased in the direction perpendicular to the feed direction. In addition, the amplitude of vibration and surface roughness showed a negative correlation. Under a given feed, the surface roughness improved as the vibration increased.

• Design & Manufacturing
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• v.17 no.3
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• pp.61-66
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• 2023

In this study, we developed a simulation methodology for a technology that rapidly cools molds by directly spraying them with CO₂ in its liquefied gaseous state. Initially, a simulation verification process was conducted using ANSYS Fluent's heat transfer analysis based on temperature values measured in prior research experiments, ensuring a comparable temperature could be calculated. Subsequently, the validated analysis method was employed to evaluate design factors that exert the most significant influence on cooling. An evaluation was conducted based on three factors: part thickness, mold thickness, and the melting temperature of material. Using a full factorial design approach, a total of 27 analyses were completed and subsequently calculated through analysis of means. The impact assessment was carried out based on the temperature values at the product's core. The results indicated that the thickness of the mold had the highest influence, while the melting temperature of material had the least.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.1
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• pp.97-107
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• 1989

An inverse self-iterative procedure is developed to estimate layer moduli of 3 layered flexible pavement structures from FWD deflection basins. The theoretical deflection basins of pavement structures obtained by full factorial design are used for the parametric study on the characteristics of deflection basins and the regression analysis. The factorial design is performed for asphalt pavement structures with stabilized base layer and granular base layer, respectively. The initially assumed layer moduli by regression equations and relations between the rate of change of moduli and deflections are used in the procedure to ensure efficiency and accuracy of self-iterative model. The SINELA computer program is used for inverse self-iterative applications to determine theoretical responses. The computer program of this procedure is coded for personal computers and is verified through numerical model tests.