• Journal of the Korean Society of Industry Convergence
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• v.14 no.4
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• pp.167-172
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• 2011

This paper investigated optimal design for slim wall mount arm for flat TV. Recently the number of flat TV sets in use went on increasing in TV market. As the flat TV sets are getting common, consumers came to need another requirements like aesthetic factor besides display performances. As the new TV sets tend to be slimmer due to aesthetic design, Wall mount also requires to be slimmer for aesthetic balance. Slim structures, however, are vulnerable to structural rigidity. In this study, slim wall mount arm has been designed by 3D CAD and DOE (Design of Experiments) and finite element analysis for optimal structural design were carried out to determine the design variables for minimize working stress of wall mount arm. Finally two optimal design conditions were selected through DOE and FEM and one of those was chosen under constraint of minimizing blanking developed length.

• Journal of Korean Society for Quality Management
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• v.26 no.4
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• pp.239-249
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• 1998

In balanced design of experiment sample size is determined to detect a certain standardized size of effect with power 1-$\beta$ at the level of significance $\alpha$. Tables (Marvin, et al (1970) and Lorenzen and Anderson(1993) and charts (Odeh and Fox(1991)) are available to determine the sample size in balanced design of experiments. To simplify those tables and charts simple MATLAB program is used to find the minimal standardized detectable difference $\delta$ when $\alpha , \beta$ and sample size are given.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1791-1792
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• 2008

휴머노이드 로봇은 기구적으로 불안정성을 내포하고 있기 때문에 이것에 대한 안정화를 하기 위해서 연구자들은 많은 방법을 사용하고 있다. 본 연구자는 실험 계획법(Design of Experiments)을 통해 본 연구자가 개발한 ISHURO-II의 발의 설계를 변경하였다. 퍼지 알고리즘을 이용하여 아랫부분에 장착된 FSR(Force Sensing Resistor)센서에서 ZMP(Zero Moment Point)의 값을 비교하여 더욱 안정된 보행이 가능하도록 하였다. 적용된 안정화 알고리즘의 성능은 VC++ 및 동역학 해석 프로그램을 이용한 시뮬레이션을 통해 검증하였다.

• Journal of the Korean Statistical Society
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• v.14 no.1
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• pp.48-55
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• 1985

In clinical trials subjects are avalible sequentially and must be assigned to treatments immediately. Completely randomized procedure for the allocation of treatments to each subject may result in severe imbalance among the number of subjects in treatment groups, especially for small experiments or interim analyses of large experiments. In this study, restricted randomization methods such as biased coin designs (Efron, 1971), permuted block design, and truncated binomial design are compared to teh completely randomized design in the presence of selection and/or accidential bias by Monte Carlo simulations.

• Journal of Environmental Science International
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• v.29 no.8
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• pp.793-800
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• 2020

The conventional development of multi-component electrodes is based on the researcher's experience and is based on trial and error. Therefore, there is a need for a scientific method to reduce the time and economic losses thereof and systematize the mixing of electrode components. In this study, we use design of mixture experiments (DOME)- in particular a simplex lattice design with Design Expert^Ⓡ program- to attempt to find an optimum mixing ratio for a three-component electrode for the high RNO degradation; RNO is an indictor of OH radical formation. The experiment included 12 experimental points with 2 center replicates for 3 different independent variables (with the molar ratio of Ru, Ti, Ir). As the Prob > F value of the 'Quadratic' model is 0.0026, the secondary model was found to be suitable. Applying the molar ratio of the electrode components to the corrected response model results is an RNO removal efficiency (%) = 59.89 × [Ru] + 9.78 × [Ti] + 67.03 × [Ir] + 66.38 × [Ru] × [Ir] + 132.86 × [Ti] × [Ir]. The R² value of the equation is 0.9374 after the error term is excluded. The optimized formulation of the ternary electrode for an high RNO degradation was acquired when the molar ratio of Ru 0.100, Ti 0.200, Ir 0.700 (desirability d value, 1).

• Transactions of The Korea Fluid Power Systems Society
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• v.6 no.4
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• pp.24-32
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• 2009

For a design of on/off solenoid actuator for valve actuating, designer must have the experimental knowledge as well as general electromagnetic formulas to design object. It is possible for theoretical knowledge to do the out-line design, but it is impossible to optimal design without experimental knowledge which only can be achieved through many repeated experiments. In addition, in present on/off type solenoid actuator field, the smaller, lightening, lower consumption power, high response time are effected as the most important design factor. So, experimental knowledge is more needed for optimal design of solenoid actuator. In this study, we derived the governing equations for optimal design of on/off solenoid actuator for valve actuating and developed a design program composed electromagnetic theories and experimental parameter values for inexperienced designers. And we proved the propriety of this program by experiments.

• Advances in aircraft and spacecraft science
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• v.6 no.6
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• pp.529-550
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• 2019

The effect of multiple process parameters on a set of continuous response variables is, especially in experimental designs, difficult and intricate to determine. Due to the complexity in aeroacoustic and vibroacoustic studies, the often-performed simple one-factor-at-a-time method turns out to be the least effective approach. In contrast, the statistical Design of Experiments is a technique used with the objective to maximize the obtained information while keeping the experimental effort at a minimum. The presented work aims at giving insights on Design of Experiments applied to aeroacoustic and vibroacoustic problems while comparing different experimental designs and approximation models. For this purpose, an experimental rig of a ducted low-pressure fan is developed that allows gathering data of both, aerodynamic and aeroacoustic nature while analysing three independent process parameters. The experimental designs used to sample the design space are a Central Composite design and a Box-Behnken design, both used to model a response surface regression, and Latin Hypercube sampling to model an Artificial Neural network. The results indicate that Latin Hypercube sampling extracts information that is more diverse and, in combination with an Artificial Neural network, outperforms the quadratic response surface regressions. It is shown that the Latin Hypercube sampling, initially developed for computer-aided experiments, can also be used as an experimental design. To further increase the benefit of the presented approach, spectral information of every experimental test point is extracted and Artificial Neural networks are chosen for modelling the spectral information since they show to be the most universal approximators.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.983-989
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• 2005

Secondary batteries with high performance are essential in widespread use of modern portable devices such as cellular phones and laptop computers. High energy density, long cycle life, and safety are some of important requirements for secondary battery. To achieve such characteristics, a mixing proportion of electrolyte solution ingredients in the battery should be carefully chosen. In this paper, using statistical design of mixture experiments (DOME), we attempt to find an optimum condition of designing the secondary battery. DOME has a distinct feature in that the experimental region is represented by simplex, rather than hypercube, because the sum of blend proportions should be unity. Several designs based upon this point have been proposed for mixture experiments. Among them, an extreme vertices design is employed in this paper because there are a couple of blend constraints to be considered. In order to investigate how the mixing proportion interacts with other manufacturing factors, a fractional factorial design is also included across the extreme vertices design. As a result, we find that the blend proportion of solution ingredients has a significant effect on battery performances. By simultaneously optimizing two battery capacities, this paper proposes an optimum blend proportion according to process factor settings.

• Archives of design research
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• v.13
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• pp.115-120
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• 1996

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.11
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• pp.1397-1405
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• 2013

The optimal rib pattern design of B-pillar trim considering occupant head protection can be determined by two methods. One is the conventional approximate optimization method that uses the statistical design of experiments (DOE) and response surface method (RSM). Generally, approximated optimum results are obtained through the iterative process by trial-and-error. The quality of results strongly depends on the factors and levels assigned by a designer. The other is a methodology derived from previous work by the authors, called the sequential design of experiments (SDOE), to reduce the trial-and-error procedure and to find an appropriate condition for using artificial neural network (ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently.