• Journal of Korean Society for Quality Management
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• v.36 no.3
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• pp.13-21
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• 2008

The orthogonality is an important property in the experimental designs. When we use nearly orthogonal arrays(for example, supersaturated designs), we need evaluate the degree of the orthogonality of given nearly orthogonal arrays. We can use the mutual information as a new criterion for evaluating and testing the degree of the orthogonality of given nearly orthogonal arrays.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.220-228
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• 2004

The orthogonality is an important property in the experimental designs. When we use nearly orthogonal arrays, we need evaluate the degree of the orthogonality of given experimental designs. Graphical methods for evaluating the degree of the orthogonality of nearly orthogonal arrays are suggested.

• Journal of the Korean Statistical Society
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• v.35 no.1
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• pp.49-61
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• 2006

Wu et al. (1992) constructed some general classes of tight asymmetric orthogonal arrays of strength 2 using the method of grouping. Rains et al. (2002) obtained asymmetric orthogonal arrays of strength 2 using the concept of mixed spread in finite projective geometry. In this paper, we obtain some new tight asymmetric orthogonal arrays of strength 2 using the concept of mixed partition in finite projective geometry.

• Journal of the Korean Statistical Society
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• v.32 no.3
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• pp.225-233
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• 2003

In this paper we make use of the parity check matrices of the codes based on inverting construction $Y_1$ to construct a number of new asymmetric orthogonal arrays with higher strength and higher number of levels using the method of construction of asymmetric orthogonal arrays given by Suen et al. (2001).

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.858-863
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• 2004

In the optimized design of an actual structure, the design variable should be selected among any certain values or corresponds to a discrete design variable that needs to handle the size of a pre-formatted part. Various algorithms have been developed for discrete design. As recently reported, the sequential algorithm with orthogonal arrays(SOA), which is a local minimum search algorithm in discrete space, has excellent local minimum search ability. It reduces the number of function evaluation using orthogonal arrays. However it only finds a local minimum and the final solution depends on the initial value. In this research, the genetic algorithm, which defines an initial population with the potential solution in a global space, is adopted in SOA. The new algorithm, sequential algorithm with orthogonal arrays and genetic algorithm(SOAGA), can find a global solution with the properties of genetic algorithm and the solution is found rapidly with the characteristics of SOA.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.885-895
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• 2004

Generally, automatic design is carried out with computer simulation and the simulation models are established by investigating the correlations between the simulation and real experiments. Therefore, the experiment results are utilized as complimentary data although they are considered to be precise. Orthogonal arrays have been adopted for discrete design. A method is proposed to directly exploit the experiment results in the design process with orthogonal arrays. Experiments are allocated to some rows of an orthogonal array and computer simulations are allocated to the others. A rule for the allocation is found to keep the orthogonality. Error analysis of the design results is performed. Mathematical examples are made to verify the validity of the proposed method. Error models are defined with the examples and the design solutions from the examples are discussed.

• 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 Mechanical Science and Technology
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• v.14 no.9
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• pp.947-955
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• 2000

This paper proposes an optimal design scheme to improve the muffler's capacity of noise reduction of the exhaust system by combining the Taguchi method and a fractional factorial design. As a measuring tool for the performance of a muffler, the performance prediction software which is developed by Oh, Lee and Lee (1996) is used. In the first stage of a design, the length and radius of each component of the current muffler system are selected as control factors. Then, the $L_{18}$ table of orthogonal arrays is adopted to extract the effective main factors. In the second stage, the fractional factorial design is adopted to take interactions into consideration, which the $L_{18}$ table of orthogonal arrays can not consider. For an optimal design, the $L_{27}$ table of orthogonal arrays with main and interaction effects is proposed and the noise factors such as temperature, background noise and humidity are analyzed for more efficient design simultaneously.

• Proceedings of the Korea Society of Design Studies Conference
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• 2002.11b
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• pp.46-47
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• 2002

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.235-244
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• 2008

Balanced arrays which are generalized orthogonal arrays, introduced by Chakravarti (1956) can be used to construct the fractional factorial designs. Especially for 2-level factorials, balanced arrays with strength 4 are identical to the resolution-V fractional designs. In this paper criteria for evaluation the degree of the orthogonality of balanced arrays of 2-levels with strength 4 are developed and some application methods of the suggested criteria are discussed. As a result, in this paper, we introduce the constructing methods of near orthogonal saturated balanced resolution-V fractional 2-level factorial designs.