• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.109-114
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• 2005

The large injection molded parts technology such as instrument panel, front and rear bumper are presented for a precision molding. Some lead time and cost are required to product these part from design to mass product. Recently, CAE is widely used in product design, mold design and analysis of molding conditions to reduce time and cost. The optimal molding conditions can be obtained by DOE(Design of Experiment). The optimal design applications with CAE and DOE have been used in small molded parts. However, application to the large molded body is not reported. In this paper, optimization of injection molding process is studied for quality control in mass production of automobile bumper. Mold temperature difference is chosen through robust design of injection molding process, the molding process being optimized in term of shrinkage and deflection. The optimal conditions through DOE are validated by using injection molding analysis.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 춘계학술대회 논문집 유기절연재료 전자세라믹 방전플라즈마 일렉트렛트 및 응용기술
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• pp.228-232
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• 2002

The rise throughput and the stability in the device fabrication can be obtained by applying chemical mechanical polishing(CMP) process in 0.18 ${\mu}m$ semiconductor device. However it does have various problems due to the CMP equipment. Especially, among the CMP components, process variables are very important parameters in determining removal rate and non-uniformity. In this paper, We studied the DOE(design of experiment) method for the optimized CMP process. Various process variations, such as table and head speed, slurry flow rate and down force, have investigated in the viewpoint of removal rate and non-uniformity. Through the above DOE results, we could set-up the optimal process parameters.

• 전기학회논문지
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• 제59권1호
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• pp.108-112
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• 2010

Design of experiment (DOE) method is employed for a systematic and highly efficient optimization of Ga-doped ZnO thin films synthesized by pulsed laser deposition (PLD) process. We sequentially adopted fractional-factorial design (FD) and central composite design (CCD) of the DOE methods. In fractional-FD stage, significant factors to make conductive electrode are found to target-substrate (T-S) distance and oxygen partial pressure. Moreover, correlation among the process factors is elucidated using surface profile modeling. Electrical properties of the GZO films grown on a glass substrate had been optimized to find that the lowest electrical resistivity of about $1.8'10^{-4}Wcm$ which was acquired with the T-S distance and the oxygen pressure of 4 cm and 7 mTorr, respectively. During the DOE-fueled optimization process, the transparency of the GZO films is ensured higher than 85 %.

• 정보저장시스템학회논문집
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• 제3권4호
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• pp.178-182
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• 2007

Topology optimization methods are classified into two methods such as the density method and the homogenization method. Those methods need to consider relationships between the material property and the density of each element in a design domain, the relaxation of the design space, etc. However, it is hard to apply on some cases due to the complexity to compose the design objective and its sensitivity analysis. In this paper, a modified topology optimization is proposed to assist designers who do not have mathematical or theoretical background of the topology optimization. In this study, optimal topology of structures can be achieved by the sequential design of experiment (DOE) and the sensitivity analysis. We conducted the DOE with an orthogonal array and the sensitivity analysis of design variables to determine sensitive variables used for connectivity between elements. The modified topology optimization method has advantages such as freedom from penalizing intermediate values and easy application with basic DOE concept.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2005년도 추계학술대회 논문집 Vol.18
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• pp.43-44
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• 2005

SU-8 is a epoxy based photoresist designed for MEMS applications, where a thick, chemically and thermally stable image is desired. But SU-8 has proven to be very sensitive to variation in processing variables and hence difficult to use in the fabrication of useful structures. In this paper, negative SU-8 photoresist processed has been characterized in terms of delamination. Based on a full factorial designed experiment. Employing the design of experiment (DOE), a process parameter is established, and analyzing of full factional design is generated to investigate degree of delamination associated with three process parameters: post exposure bake (PEB) temperature, PEB time, and exposure energy. These results identify acceptable ranges of the three process variables to avoid delamination of SU-8 film, which in turn might lead to potential defects in MEMS device fabrication.

• Journal of information and communication convergence engineering
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• 제3권4호
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• pp.191-194
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• 2005

SU-8 is a epoxy based photoresist designed for MEMS applications, where a thick, chemically and thermally stable image are desired. However SU-8 has proven to be very sensitive to variation in processing variables and hence difficult to use in the fabrication of useful structures. In this paper, negative SU-8 photoresist processed has been characterized in terms of delamination, based on a full factorial designed experiment. Employing the design of experiment (DOE), a process parameter is established, and analyzing of full factorial design is generated to investigate degree of delamination associated with three process parameters: post exposure bake (PEB) temperature, PEB time, and exposure energy. These results identify acceptable ranges of the three process variables to avoid delamination of SU-8 film, which in turn might lead to potential defects in MEMS device fabrication.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 춘계학술대회
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• pp.253-258
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• 2010

The paper reviews the methodologies of confirmatory data analysis(CDA) and exploratory data analysis(EDA) in statistical quality control(SQC), design of experiment(DOE) and reliability engineering(RE). The study discusses the properties of flexibility, openness, resistance and reexpression for EDA.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.395-396
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• 2006

This paper presents the optimal design of Robot-Arm part use Design of Experiment(DOE). The DOE(Design of Experiment)was conducted to find out main effect factors for design of Robot-Arm part. In this design of Robot-Arm, 5 control factors include numbers of 4 level are selected and we make out L16 orthogonal array. Using this orthogonal array, find out optimal value and main effect factors of object function for design of Robot-Arm part by 16 times of test. We evidence this optimal value by using CATIA V5 Analysis.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1846-1851
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• 2003

Approximate optimization has become popular in engineering field such as MDO and Crash analysis which is time consuming. To accomplish efficient approximate optimization, accuracy of approximate model is very important. As surrogate model, Kriging have been widely used approximating highly nonlinear system . Because Kriging employs interpolation method, it is adequate for deterministic computer simulation. Because there are no random errors and measurement errors in deterministic computer simulation, instead of classical DOE ,space filling experiment design which fills uniformly design space should be applied. In this work, various space filling designs such as maximin distance design, maximum entropy design are reviewed. And new design improving maximum entropy design is suggested and compared.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.708-713
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• 2000

The design of experiment(DOE) is getting more attention in the engineering community since it is easy to understand and apply. Recently, engineering designers are adopting DOE with orthogonal arrays when they want to design products in a discrete design space. In this research, a design flow with orthogonal arrays is defined fur structural design according to the general DOE. The design problem is defined as a general structural optimization problem. Sensitivity information is evaluated by the analysis of variance(ANOVA), and an optimum design is determined from analysis of means(ANOM). Interactions between design variables are investigated to achieve additivity which should be valid in DOE. When strong interactions exit, a method is proposed. Some methods to consider the problem are suggested.