• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.735-741
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• 2011

In the early phase of vehicle development, CAE is conducted as tool for vehicle performance assessment. To maintain acceptable road noise performance, solution for reduced vehicle sensitivity is required. Chassis interface dynamic stiffness characteristics are key component to isolating vibration and noise of road from the vehicle interior. This research provide how to set up the optimized dynamic characteristics under noise effect through DFSS study. CAE-based DOE is performed to build prediction math model, CMS process involves DOE to achieve very fast run times while giving results very comparable. Minimized $95^{th}$ percentile of performance distribution is applied to minimize vehicle sensitivity and road noise levels variation during the optimization process. Finally, the results of optimization were reviewed for performance and robustness.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.3
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• pp.502-506
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• 2012

Air bearing is characterized by its extremely low friction and cleanliness such that it is widely used especially for spindles with ultra-high rotational speed at several tens of thousands rpm. This paper contributes to design of a static radial air bearing suggesting numerical analysis to anticipate its performances. The numerical analysis is an iteration method based on finite difference formulation of the Reynolds equation. A prototype air bearing has been designed and manufactured. Its load capacity has been measured and compared with the numerical solutions. The result shows good consistency between the experiment and theory, which informs that the numerical analysis can be used as an useful tool to anticipate the performances. Effects of design variables on the bearing performance have been examined by Taguchi's experimental methods using orthogonal array. Number of holes for supplying pressurized air, clearance between shaft and bearing, the hole diameter and bearing length are chosen for the design variables. The result shows that the clearance and the bearing length are the most influential variables while the others can be considered as almost negligible.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.1
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• pp.113-120
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• 2013

This paper proposes a design optimization approach for core of solenoid actuators by combining optimization techniques with the finite element method (FEM). A solenoid is an important element part which hydraulically controls a transmission system, etc. The demanded feature of the solenoid is that it performs an electromagnetic force output being constant regardless of the stroke and being proportional to coil current. The plunger compresses a spring with a minimum force of 12 N over an 1.7 mm travel. The orthogonal array, analysis of variance (ANOVA) techniques and response surface optimization, are employed to determine the main effects and their optimal design variables. The methodology is demonstrated as a optimization tool for the core design of a solenoid actuator.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.05a
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• pp.207-212
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• 2009

In order to optimize the press formability of incremental sheet forming for complex shape (e.g human face), a combination of both CAM and FEM simulation, is implemented and evaluated from the histories of stress and strain value by means of finite element analysis. Here, the results, using ABAQUS/Explicit finite element code, are compared with fracture limit curve (FLC) in order to predict and optimize the press formability by changing parameters of tool radius and tool down-step according to the orthogonal array of Taguchi's method. Firstly, The CAM simulation is used to create cutter location data (CL data). This data are then calculated, modified and exported to the input file format required by ABAQUS through using MATLAB programming. The FEM results are implemented for negative incremental sheet forming and then investigate by experiment.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.190-196
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• 2001

This study aims to develop three types of the visual fields: stationary field, eye field, and head field, which are classified depending upon the eye and head movements. A visual experiment taking target size, target color, and meridian into account was conducted, in which the L32 orthogonal array was employed. The results showed that target size and meridian were significant at ${\alpha}$=0.01 in all three visual fields. Contrary to expectation, target color was significant at ${\alpha}$=0.10 only in the head field. Furthermore, the differences in size of the head field depending upon four target colors were negligibly small. Three linear regression models were provided to generate visual fields which are appropriate for given visual task's characteristics. In addition, a simple method using adjusting factor was also proposed so that anyone without knowledge for human factors/ergonomics can easily generate and use them when designing or evaluating visual tasks. It is expected that the visual fields presented in this study can be easily used even by non-ergonomic experts in real situations due to their simplicity.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.7
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• pp.674-681
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• 2011

In the early phase of vehicle development, CAE is conducted as tool for vehicle performance assessment. To maintain acceptable road noise performance, solution for reduced vehicle sensitivity is required. Chassis interface dynamic stiffness characteristics are key component to isolating vibration and noise of road from the vehicle interior. This research provide how to set up the optimized dynamic characteristics under noise effect through DFSS study. CAE-based DOE is performed to build prediction math model, CMS process involves DOE to achieve very fast run times while giving results very comparable. Minimized 95th percentile of performance distribution is applied to minimize vehicle sensitivity and road noise levels variation during the optimization process. Finally, the results of optimization were reviewed for performance and robustness.

• Design & Manufacturing
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• v.13 no.3
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• pp.53-58
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• 2019

This paper presents Artificial Neural Network(ANN) method to predict maximum injection pressure of injection molding machine and weights of injection molding products. 5 hidden layers with 10 neurons is used in the ANN. The ANN was conducted with 5 Input parameters and 2 response data. The input parameters, i.e., melt temperature, mold temperature, fill time, packing pressure, and packing time were selected. The combination of the orthogonal array L27 data set and 23 randomly generated data set were applied in order to train and test for ANN. According to the experimental result, error of the ANN for weights was $0.49{\pm}0.23%$. In case of maximum injection pressure, error of the ANN was $1.40{\pm}1.19%$. This value showed that ANN can be successfully predict the injection pressure and the weights of injection molding products.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.6
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• pp.10-16
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• 2021

Drilling is a crucial process that takes up a significant amount of weight during machining operations. In addition, drill tip-type tools and related operations have been developed for manufacturing industries to achieve economic efficiency. In this study, SM45C carbon steel, widely used for machine structures, was utilized as the working material after quenching and tempering. Insert-tip types of carbide tools, such as TiN and TiAlN, were used as tool materials. Drilling conditions such as the spindle revolution, feed rate, step of cut, and tool diameter were used to measure roughness, roundness, and straightness using the orthogonal array table statistical method. The surface roughness, roundness, and straightness characteristics based on the conditions were analyzed using ANOVA. The results showed that the spindle speed and feed rate were the main factors influencing carbide insert-tip drilling under the same conditions as the experimental conditions.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1037-1045
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• 2022

In this study, nanoscale Al₂O3 ceramic particles were used due its exceptionally high hardness characteristics, chemical stability, and wear resistance properties. These nanoparticles will be used to investigate the optimal process conditions for the electro co-deposition of the Ni-Al₂O₃ composite coatings. A Watts bath electrolytic solution of a controlled composition along with a fixed agitation speed was used for this study. Whereas the current density, the pH value, temperature and concentration of the nano Al₂O₃ particles of the electrolyte were designated as the manipulative variables. The experimental design method was based on the orthogonal array to find the optimum processing parameters for the electro co-deposition of Ni-Al₂O₃ composite coatings. The result of confirmation experimental based on the optimal processing condition through the analysis of variance ; EDX analysis found that the ratio of alumina increased to 8.65 wt.% and subsequently the overall hardness increased to 983 Hv. Specially, alumina were evenly distributed on Nickel matrix and particles were embedded more firmly and finely in Nickel matrix.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.153-159
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• 2011

The MUSIC (MUltiple SIgnal Classification) method estimates the directions of arrival (DOAs) of the signals impinging on a sensor array based on the fact that the noise subspace is orthogonal to the signal subspace. In the conventional MUSIC, an estimate of the basis for the noise subspace is obtained by eigendecomposing the sample matrix, which is computationally expensive. In this paper, we present a simple DOA estimation method which finds an estimate of the signal subspace basis directly from the columns of the sample matrix from which the noise power components are removed. DOA estimates are obtained by searching for minimum points of a cost function which is defined using the estimated signal subspace basis. The minimum points are efficiently found through the Brent method which employs parabolic interpolation. Simulation shows that the simple estimation method virtually has the same performance as the complex conventional method based on the eigendecomposition.