• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.245-253
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• 2011

Powers of rank transformed statistic for testing main effects and interaction effects for $2{\times}2$ factorial design in randomized complete block design are very superior to powers of parametric statistic without regard to the block size, composition method of effects and the type of population distributions such as exponential, double exponential, normal and uniform. $2{\times}2$ factorial design in RCBD increases error effects and decreases powers of parametric statistic which results in conservativeness. However powers of rank transformed statistic maintain relative preference. In general powers of rank transformed statistic show relative preference over those of parametric statistic with small block size and big effect size.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.57-65
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• 2007

Along with the development of power electronics and magnetic materials, permanent magnet (PM) brushless direct current (BLDC) motors are now widely used in many fields of modern industry BLDC motors have many advantages such as high efficiency, large peak torque, easy control of speed, and reliable working characteristics. However, Compared with the other electric motors without a PM, BLDC motors with a PM have inherent cogging torque. It is often a principle source of vibration, noise and difficulty of control in BLDC motors. Cogging torque which is produced by the interaction of the rotor magnetic flux and angular variation in the stator magnetic reluctance can be reduced by sinusoidal air-gap flux density waveform due to reduction of variation of magnetic reluctance. Therefore, this paper will present a design method of magnetizing system for reduction of cogging torque and low manufacturing cost of BLDC motor with isotropic bonded neodynium-iron-boron (Nd-Fe-B) magnets in ring type by sinusoidal air-gap flux density distribution. An analytical technique of magnetization makes use of two-dimensional finite element method (2-D FEM) and Preisach model that expresses the hysteresis phenomenon of magnetic materials in order for accurate calculation. In addition, For optimum design of magnetizing fixture, Factorial design which is one of the design of experiments (DOE) is used.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.15-24
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• 2012

For the construction of fractional factorial designs, the various arrays can be widely used. In this paper we review the statistical properties of fractional designs constructed by two arrays such as orthogonal array and partially balanced array, and develop a quick and easy method for analyzing unreplicated saturated designs. The proposed method can be characterized that we control the error rate by experiment-wise way and exploit the multivariate Student $t$-distribution. Especially the proposed method can be used efficiently together with some exploratory analysis methods, such as half normal probability plot method.

• Analytical Science and Technology
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• v.20 no.5
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• pp.370-382
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• 2007

In this study, solid-phase microextraction (SPME) technique using GC/FID was studied as a possible alternative to liquid-liquid extraction for the analysis of EGBE, DGBE, DBM and TGME in water, and an optimization condition of trace analysis of EGBE, DGBE, DBM and TGME using the factorial design was described. Experiments used a fractional factorial design method followed by central composite design allowing optimization of a number of factors as well as statical analysis of results. The response surface analysis showed that the extraction efficiency can be described by a second-order polynomial equation in which the salts concentration, extraction temperature, extraction time and sonication time are the major influences. Using DOE, a new data-dependent method was developed that improved the quantity of confidently analyzed EGBE, DGBE, DBM and TGME in water samples.

• International Journal of Korean Welding Society
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• v.1 no.2
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• pp.36-44
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• 2001

To get the appropriate welding process variables, mathematical modeling in conjunction with many experiments is necessary to predict the magnitude of weld bead shape. Even though the experimental results are reliable, it has a difficulty in accurately predicting welding process variables for the desired weld bead shape because of nonlinear and complex characteristics of welding processes. The welding condition determined for the desired weld bead shape may cause the weld defect if the welding current/voltage/speed combination is improperly selected. In this study, the $2^{n-1}$ fractional factorial design method and correlation parameter were used to investigate the effect of the welding process variables on the fillet joint shape, and the multiple non-linear regression analysis was used for modeling the gas metal arc welding(GMAW）parameters of the fillet joint. Finally, a fuzzy rule-based method and a neural network method were proposed so that the complexity and non-linearity of arc welding phenomena could be effectively overcome. The performance of the proposed neuro-fuzzy system was evaluated through various experiments. The experimental results showed that the proposed neuro-fuzzy system could effectively check the welding conditions as to whether or not weld defects would occur, and also adjust the welding conditions to avoid these weld defects.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.5
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• pp.545-552
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• 2015

The heat generation in PEMFC is proportional to the electrical power output. Therefore, when the fuel cell produced the maximum output, the maximum heat was generated. In order to maintain the performance of the fuel cell, thermal management is as important as pressure and humidity conditions of the reactive gas. In this study, considering the thermal management for the maximum output operation, the optimal cooling channel design specifications of bipolar plate are found for the highest cooling performance. In the current bipolar plate research, many studies focused on analyzing various factors individually but there is no more study on the interaction between design factors. In this study, the heat transfer was simulated by COMSOL Multiphysics with the main design factors which are designated shape, width and rib length. One of the experimental design methods, general full factorial design method, was used to analyze the main factor and interaction on average temperature and maximum temperature for the design specification of fuel cell bipolar plate. When analysis result shows that all of these three factors are highly important, it can confirm that the interaction occurs between the factors.

• International Journal of Korean Welding Society
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• v.3 no.2
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• pp.15-23
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• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Welding and Joining
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• v.18 no.5
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• pp.63-69
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• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.5
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• pp.81-87
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• 2015

In this paper, the finite element method was used for the flow and strength analysis of aluminum alloy under friction stir welding. The simulations were carried out using Sysweld s/w, and the modeling of the sheet was executed using Unigraphics NX6 s/w. The welding variables for the analysis were the shoulder diameter, rotating speed, and welding speed of the tool. Additionally, a three-way factorial design method was applied to confirm the effect of the welding variables on the flow and strength analysis with variance analysis. From these results, the rotating speed had the greatest influence on the maximum temperature, and the maximum temperature was $578.84{\pm}12.72$ at a confidence interval of 99%. The greater the rotating speed and shoulder diameter, the greater the difference between maximum and minimum temperature. Furthermore, the shoulder diameter had the largest influence on von Mises stress, and the von Mises stress was $184.54{\pm}12.62$ at a confidence interval of 99%. In addition to the increased shoulder diameter, welding speed, and rotating speed of the tool increased the von Mises stress.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.10
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• pp.685-691
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• 2015

In this work, to identify effective parameter for performance of piezoelectric jetting dispenser, experimental investigation is carried out based on design of experiment. After preparing jetting dispenser using two stack-type piezoelectric actuators, basic working principle of the jetting dispenser is described. Eight operating conditions are chose as main factors and it is assumed that each factor has two levels. To reduce number of experiments for performance evaluation, the experimental sets are designed based on factional factorial design method. Experimental setup is established and the weight of single dot is measured by using precision scale. The main and interaction effects of factors are analyzed using commercial statistical program and optimal operating condition for small amount and small variation of weight of dispensed single dot are determined.