• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.483-495
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• 2007

In a general fractional factorial design, the n-levels of a factor are coded by the $n^{th}$ roots of the unity. Pistone and Rogantin (2007) gave a full generalization to mixed-level designs of the theory of the polynomial indicator function using this device. This article discusses the optimal blocking scheme for nonregular designs. According to hierarchical principle, the minimum aberration (MA) has been used as an important criterion for selecting blocked regular fractional factorial designs. MA criterion is mainly based on the defining contrast groups, which only exist for regular designs but not for nonregular designs. Recently, Cheng et al. (2004) adapted the generalized (G)-MA criterion discussed by Tang and Deng (1999) in studying $2^p$ optimal blocking scheme for nonregular factorial designs. The approach is based on the method of replacement by assigning $2^p$ blocks the distinct level combinations in the column with different blocks. However, when blocking level is not a power of two, we have no clue yet in any sense. As an example, suppose we experiment during 3 days for 12-run Plackett-Burman design. How can we arrange the 12-runs into the three blocks? To solve the problem, we apply G-MA criterion to nonregular mixed-level blocked scheme via the mixed-level indicator function and give an answer for the question.

• Food Engineering Progress
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• v.15 no.2
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• pp.97-115
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• 2011

A review about the application of response surface methodology in the optimization of food technology is presented. The theoretical principles of response surface methodology and steps for its application are described. The response surface methodologies : three-level full factorial, central composite, Box-Behnken, and Doehlert designs are compared in terms of characteristics and efficiency. Furthermore, recent references of their uses in food technology are presented. A comparison between the response surface designs (three-level full factorial, central composite, Box-Behnken and Doehlert design) has demonstrated that the Box-Behnken and Doehlert designs are slightly more efficient than the central composite design but much more efficient than the three-level full factorial designs.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.E2
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• pp.83-91
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• 2008

This work investigated the methodology to simultaneously optimize the ozone and relative humidity composition for the $NO_x$ degradation using soil biofilter. Experiments were made as a function of inlet ozone concentration ($0{\sim}1,770\;ppb$) and relative humidity ($38{\sim}81%$). Factorial design ($2^2+3$) and response surface methodology by central composite designs were used to examine the role of two factors and optimal response condition on $NO_x$ degradation. It was found that a second-order response surface model can properly interpret the experimental data with an $R^2$-value of 0.9730 and F-value of 71.83, based on which the maximum $NO_x$ degradation was predicted up to 92.8% within our experimental conditions.

• International Journal of Korean Welding Society
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• v.1 no.1
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• pp.44-50
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• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels 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 in less than 40 experiments.

• Journal of the Korean Electrochemical Society
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• v.17 no.3
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• pp.193-200
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• 2014

Research on flow channel designs of the separate plates is necessary to improve the PEMFC performance. On concerning the performance improvement of PEMFC, many recent studies have been made on the interdigitated flow channel using forced convection. In this paper, the interdigitated flow channel is similarly applied on the parallel flow channel with a baffle or baffles. Numerical analysis is performed by using a commercial multiphysics program, which is called COMSOL, on the parallel channel with the fully blocked baffle(FBB) and there are three variables, the position of baffle, flow direction and flow velocity. Each power of the variables is resulted from the fixed 0.5V, the voltage from 80 percents of the maximum power. Finally, based on the full factorial designs(FFD), one of the design of experiments(DOE), each factor which has several levels lead to the conclusion. The analysis of the main effects and interactions of the factors is useful to find the most influenced factor to improve the power.

• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.59-74
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• 2007

Computer simulation models are in general quite complex and time-consuming to run, and therefore, a simpler meta-model is usually constructed for further analysis. In this paper, JANUS, a war-game simulator, is used to describe a certain tank combat situation. Then, second-order response surface and artificial neural network meta-models are developed using the data from eight different experimental designs. Relative performances of the developed meta-models are compared in terms of the mean squared error of prediction. Computational results indicate that, for the given problem, the second-order response surface meta-model generally performs better than the neural network, and the orthogonal array-based Latin hypercube design(LHD) or LHD using maximin distance criterion may be recommended.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1183-1188
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• 2013

The reliability of hydraulic equipment used in power plants is especially important because failures that occur in the power plant can have a great ripple effect on human lives and financial losses. In this study, specimens using the materials used in the spool and sleeve of hydraulic valves of power plants have been produced, heat-treated, and tested under the precipitation conditions of phosphate ester hydraulic fluid with a variety of conditions. 23 full factorial designs have been applied to evaluate the significance of factors that affect the wear loss of the specimen, specifically, the load, velocity, and temperature. The significance evaluation was performed on the main effects and two-way interactions for wear loss based on the experiment results, and the mathematical equations between the wear loss and the three factors were derived from the analysis results.

• Journal of Industrial Technology
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• v.17
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• pp.313-322
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• 1997

As the weight of trucks increases, the need for concrete pavement also increases. Therefore, the addition of fly-ash may improve the properties of pavement concrete as well as recycle fly-ash. A full factorial experiment was performed using the primary variables, such as water-cement ratio, fly-ash substitution ratio, and maximum size of coarse aggregate, as a preliminary study for optimum mixture design for pavement concrete. The results of preliminary study indicates that the addition of fly-ash is the most important factor determining concrete strength, followed by the maximum size of coarse aggregate and water-cement ratio. It, also, shows the relative importance of fly-ash substitution ratio, compared to the water-cement ratio, and the interaction effects between the primary variables. Optimum mixture designs for pavement concrete incorporating fly-ash, that satisfied the target responses, were proposed in terms of fly-ash substitution ratio, water cement ratio and maximum size of coarse aggregate.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.513-516
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• 2004

Evolutionary operation is useful to improve on-line full-scale manufacturing processes by systematically changing the levels of the process variables while meeting production schedule. Evolutionary operation was developed using two or three process variables for process operators who are not good at statistics. Recently, when a product is developed, it is very important for the engineers to make the production line stable as soon as possible. And there are many causes which have influences to the product performance. This paper presents an evolutionary operation procedure with many process variables using saturated two level fractional factorial designs including Plackett-Burman design.