• Journal of the Korean Society for Precision Engineering
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• v.29 no.2
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• pp.193-200
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• 2012

Wheel loader is one of the construction machinery capable of variety of tasks and the demand on functional diversity and structural reliability is growing. As a study on the optimal shape design of front axle for wheel loader through the design of experiments, this paper assessed the design parameters affecting the maximum stress. As a result, a value of 126.77 MPa of minimum stress was obtained, and optimal factors showed the values of w = 100.0 mm, ${\theta}=40^{\circ}$ and R = 118 mm. It showed an accuracy of 98.7% compared with the structural analysis.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.322-327
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• 2023

A design of experiments was evaluated in optimizing MOF-5 synthesis for acetylene adsorption. At first, mixture design was used to optimize precursor concentration, terephthalic acid, zinc acetate dihydrate and N,N-dimethylformamide. More specifically, 13 conditions with various molar ratios were designed by extreme vertices design method. After preparing the samples, XRD, N₂ physisorption and SEM analysis were performed for their characterization. Moreover, acetylene adsorption experiments were carried out over the samples under identical conditions. The optimal precursor composition for MOF-5 synthesis was predicted on a molar basis as follows: terephthalic acid : acetate dihydrate : dimethylformamide = 0.1 : 0.4 : 0.5. Thereafter, multi-level factorial design was designated to investigate the effect of synthesis reaction conditions such as temperature, time and stirring speed. By the statistical analysis of 18 samples designed, 4 reaction parameters were determined for additional adsorption experiments. Therefore, MOF-5 prepared under the synthesis time and temperature of 100 ℃ and 12 h, respectively, showed the maximum adsorption capacity of 15.1 mmol/g.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1960-1965
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• 2001

In the practical design, it is important to extract the design space information of a complex system in order to optimize the design because the design contains huge amount of design conflicts in general. In this research FEA (finite element analysis) has been successfully implemented and integrated with a statistical approach such as DOE (design of experiments) based RSM (response surface model) to optimize the thermal deformation of an automotive disk brake. The DOE is used for exploring the engineer's design space and for building the RSM in order to facilitate the effective solution of multi-objective optimization problems. The RSM is utilized as an efficient means to rapidly model the trade-off among many conflicting goals existed in the FEA applications. To reduce the computational burden associated with the FEA, the second-order regression models are generated to derive the objective functions and constraints. In this approach, the multiple objective functions and constraints represented by RSM are solved using the sequential quadratic programming to archive the optimal design of disk brake.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.258-266
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• 2008

The conventional approximate optimization method, which uses the statistical design of experiments(DOE) and response surface method(RSM), can derive an approximated optimum results through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. The purpose of this study is to propose a new technique, which is called a sequential design of experiments(SDOE), to reduce a 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. The suggested algorithm has been applied to various mathematical examples and a structural problem.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.1
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• pp.24-32
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• 2016

The mortality rate of car-pedestrian accidents is quite high, compared to the frequency of accidents. Researches on pedestrian protection are being actively performed worldwide. The A-pillar and lower part of the wind shield cause the most serious damage to the pedestrians. Typical devises to protect the pedestrians are the hood lift system and pedestrian airbag. The design of such devices for an sport utility vehicle is performed based on a design process using design of experiments (DOE). The design results are obtained by an orthogonal array (OA), analysis of mean (ANOM) and analysis of variance (ANOVA). A metamodel is also used in the design process.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.1
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• pp.38-46
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• 2008

Design technology and speciality production technology to manufacture high quality valve are insufficient in Korea. In order to design the experiments using Taguchi method and Variational Technology Also, from verification of the response model with optimized results was confirmed that usefulness and reliance of application Taguchi method and Variational Technology to structural's optimum design using Taguchi method and Variational Technology.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.799-806
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• 2004

This paper presents a scheme for finding an optimal combination of design parameters affecting on the handling performance of a large truck using design of experiments. The average of the sum of peak-to-peak roll angles at the first and second part of the double lane is used as an objective function for design of experiments. Six design parameters are selected from all possible parameters affecting on the handling performance. The table of orthogonal arrays is made by 27 times simulations. A computational model of a large truck is developed by MSC/NASTRAN and MSC/ADAMS, and verified the reliability of it with the results of vehicle tests performed in a double lane change course. It is used for the simulations. Analyses of variance and factor effect of the table of orthogonal arrays are performed. This paper proposes an optimal combination of those six design parameters for improving the handling performance of the large truck.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.11
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• pp.1179-1185
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• 2013

In this study, the design optimization of the automotive side member is performed to maximize the crash energy absorption efficiency per unit weight. Design parameters which seriously influence on the frontal crash performance are selected through the sensitivity analysis using the Plackett-Burman design method. And also the design variables, which are determined from the sensitivity analysis, are optimized by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). The other is a methodology derived from previous work by the authors, which is called sequential design of experiments (SDOE), to reduce a trial and error procedure and to find an appropriate condition for using micro-genetic algorithm. The proposed optimization technique shows that the automotive side member structure can be designed considering the frontal crash performance.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.408-413
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• 2001

The structural optimization is carried out in the continuous design space or discrete design space. Methods for discrete variables such as genetic algorithms are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete design space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions for constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• Journal of Magnetics
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• v.20 no.2
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• pp.193-200
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• 2015

Direct-acting solenoid valves are used in the automotive industry due to their simple structure and quick response in controlling the flow of fluid. We performed an optimization study of response time in order to improve the dynamic performance of a direct-acting solenoid valve. For the optimal design process, we used the commercial optimization software PIAnO, which provides various tools for efficient optimization including design of experiments (DOE), approximation techniques, and a design optimization algorithm. 35 sampling points of computational experiments are performed to find the optimum values of the design variables. In all cases, ANSYS Maxwell electromagnetic analysis software was used to model the electromagnetic dynamics. An approximate model generated from the electromagnetic analysis was estimated and used for the optimization. The best optimization model was selected using the verified approximation model called the Kriging model, and an optimization algorithm called the progressive quadratic response surface method (PQRSM).