• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.759-766
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• 2000

In order to design fractional factorial experiments which include some debarred combinations, we should select defining contrasts so that those combinations are to be excluded. Choi(1999) presented a method of selectign defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations. In this paper, we extend Choi's method to general p-level fractional factorial experiments to select defining contrasts which cold exclude some debarred combinations.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.31-45
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• 2021

Purpose: A noncentral composite design method is to be developed to explore farther region for the first factorial design. A general guideline for sequential experimentation is provided. Methods: (1) A non-overlapping noncentral composite design (NNCD) is developed, in which the second factorial design shares one design point that indicates the best response value in the first factorial design. (2) Four composite designs are compared in terms of the four design evaluation criteria, which are D-, A, G, and I-optimality. (3) A follow-up design strategy is suggested based on the interaction effect, direction of improvement, number of factors. Results: (1) NNCD and model building method are presented, which is useful for exploring farther region from first factorial design block. (2) The performances of the four composite designs are compared. (3) A follow-up design strategy is suggested. Conclusion: (1) NNCD will be useful to explore farther region for the first factorial design. (2) A follow-up design strategy can be beneficial to the experimental practitioners for product and process design and improvement.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.307-315
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• 2001

The purpose of this study was to provide the evaluation and prediction of strengths of SB latex modified concrete(LMC) using a statistical method and factorial experimental design method. The main experimental variables were as follows ; W/C ( 4 levels ; 31, 33, 35, 42%), S/a( 2 levels ; 55, 58%) and L/C(2 levels ; 5, 15%). The compressive strength and flexural strength of LMC were selected as a factor of response. The statistical method was carried out to analyze the results, together with factorial experimental design method and response surface method. The analysis showed that if L/C had been 15%, W/C appeared to be around 33% to achieve the design strength of $350kgf/cm^2$. In this case, the flexural strength and the slump came to around $68kgf/cm^2$ and 18cm, respectively. Eventhough the L/C varied, the design strength and W/C could be predictable together with slump value and flexural strength. As a result of series of experiments in this study, W/C and L/C were proved to be the main factors influencing on the compressive and flexural strength of LMC. Both of strength and slump values could be predictable from the mixing proportion of LMC.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.249-258
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• 1993

It is well known that design matrix X for any factorial design can be represented by a product $X = TX_o$ where T is replication matrix and $X_o$ is the corresponding balanced design matrix. Since $X_o$ consists of regular arrangement of 0's and 1's, we can easily find the spectral decomposition of $X_o',X_o$. Also using this we propose an efficient algorithm for computing the orthogonal projection matrix for a balanced factorial design.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.121-129
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• 1999

Recently, the regulations from the govemment and the concems of the people give rise to the interest in exhaust noise of passenger car as much as other vehicles. The exact analysis of various mufflers is needed to reduce the level of exhaust noise. In this paper, we propose a design to improve the mufflers capacity by reducing noise of exhaust system combining Taguchi method and fractional factorial design. In order to measure the performance of a muffler, the performance prediction software which is developed by the Dept. of Automotive Engineering at Hanyang University is used. From the current muffler system we select control factors such as lenght and radius of each component that are thought to be effective on capacity of muffler. Factors are arranged using L18, L27 table of orthogonal array and the fractional factorial design for analysis. We find some significant interaction effects using 1/3 fractional factorial design and accomplish the reduction of noise from the muffler.

• 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 Safety Management and Science Conference
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• 2009.04a
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• pp.423-427
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• 2009

This study proposes the generation mechanism of various design matrix using generalized linear model for design of experiment. Design generation method of GLM analysis, factorial design(FD) with center points, ANOVA design with lack-of-fit test, and response surface design are introduced. In central composite(CC) design, orthogonal blocking and fractional factorial design(FFD) are presented. We compare the design of Box-Benhken(BB) and face-centred central compsite design.

• Journal of the Korea Concrete Institute
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• v.16 no.2 s.80
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• pp.269-275
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• 2004

Factorial design method is applied to investigate the effects of various factors simultaneously rather than to conduct a series of single-factor experiment. As the results, frost resistance of the concrete specimens, in both W/C ratio of 0.28 and 0.35, was highly affected by the type of coarse aggregate that is, andesite produced more durable concrete than the limestone. Durability factor of the specimens, with W/C ratio of 0.28, which were demolded after I day and transferred to the curing room was higher than those demolded after 2 days. This stated the efficiency of the high early curing in high strength concrete.

• Journal of the Semiconductor & Display Technology
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• v.12 no.1
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• pp.47-51
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• 2013

The screen printing is a process that is widely used in manufacturing process of various fields such as flexible devices, portable multimedia devices, OLED, and the solar cell. The screen printing method has been studied as a method for forming the high precision micro-pattern, making the low-cost manufacturing process and reducing cost through improvement of productivity. It is applicable to deposit and forming the pillars which are one of the core element for comprising vacuum glazing. In this paper, by using the paste of the glass frit base, the screen printing was performed. We analyzed the effect for the printing process to deposit pillar paste on the screen printing parameters by the factorial experimental design. The polynomial predicting the volume of the printed supporting pillars was drawn by using screen printing.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.695-706
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• 1999

When fractional factorial experiments contain some infeasible treatment combinations called debarred combinations we should construct experimental designs so that those debarred combinations are to be excluded by selecting defining contrasts appropriately. By applying Franklin(1995)'s procedure for selecting defining contrasts to Cheng and Li(1993)'s method this paper presents a method of selecting defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations.