• 제목/요약/키워드: Factorial design of experiments

검색결과 193건 처리시간 0.029초

폐지섬유보강 시멘트 복합체의 최적배합비 도출 (Optimum Mix Design for Waste Newsprint Paper Fiber Reinforced Cement Composites)

  • 원종필;배동인;박찬기;박종영
    • 콘크리트학회논문집
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    • 제13권4호
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    • pp.346-353
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    • 2001
  • 본 연구는 얇은 시멘트판 제품의 보강재로써 건조공정에 의해 생산된 폐지섬유의 최적 배합비를 도출하기 위하여 수행되었다. 이를 위해 순수 목질섬유 대비 폐지섬유의 대체수준을 세분화하여 실험을 실시하였으며, 슬러리-탈수 공법을 사용하여 폐지섬유보강 시멘트 복합체를 제조하였다. 본 연구는 실험적 연구와 반응표면 분석법을 활용한 통계적 분석을 통해 공정인자(가압, 비가압)과 섬유보강재 조건(섬유혼입율, 순수섬유 대체수준)을 최적화하였다. 최적화된 재생 폐지섬유 시멘트 복합체를 기술적으로 분석하였으며, 그 결과, 폐지섬유보강 시멘트 복합체의 성능과 경제적 측면에서 폐지섬유의 재활용이 가능하리라 판단된다.

탑재비행시험을 위한 무인헬기 연료 소모량 예측모형 연구 (A Study on the Prediction Model of Unmanned Helicopter Fuel Consumption for the Captive Flight Test)

  • 김지수
    • 한국콘텐츠학회논문지
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    • 제19권7호
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    • pp.436-443
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    • 2019
  • 본 논문의 목적은 탑재비행시험 간 무인헬기 연료 소모량에 영향을 미치는 인자들의 영향정도와 상관관계를 분석하여 예측모형을 수립하는 것이다. 본 연구에서는 실험계획법을 활용하여 4인자 2수준 완전요인실험을 설계하여 실험을 수행하였고, 결과 값을 분석하여 인자들의 주 효과와 교호작용을 도출하고 회귀분석을 통해 예측모형을 수립하였다. 본 연구에서 도출한 결과를 활용하여 효율적인 탑재비행시험 및 전자시험장 시험 능력 향상에 기여할 것으로 기대된다.

Machine learning modeling and DOE-assisted optimization in synthesis of nanosilica particles via Stöber method

  • Moradi, Hiresh;Atashi, Peyman;Amelirad, Omid;Yang, Jae-Kyu;Chang, Yoon-Young;Kamranifard, Telma
    • Advances in nano research
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    • 제12권4호
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    • pp.387-403
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    • 2022
  • Silica nanoparticles, which have a broad range of sizes and specific surface features, have been used in many industrial applications. This study was conducted to synthesize monodispersed silica nanoparticles directly from tetraethyl orthosilicate (TEOS) with an alkaline catalyst (NH3) based on the sol-gel process and the Stöber method. A central composite design (CCD) is used to build a second-order (quadratic) model for the response variables without requiring a complete three-level factorial experiment. The process was then optimized to achieve the minimum particle size with the lowest concentration of TEOS. Dynamic light scattering and scanning electron microscopy were used to analyze the size, dispersity, and morphology of the synthesized nanoparticles. After optimization, a confirmation test was carried out to evaluate the confidence level of the software prediction. The results revealed that the predicted optimization is consistent with experimental procedures, and the model is significant at the 95% confidence level.

뉴런 활성화 경사 최적화를 이용한 개선된 플라즈마 모델 (An improved plasma model by optimizing neuron activation gradient)

  • 김병환;박성진
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.20-20
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    • 2000
  • Back-propagation neural network (BPNN) is the most prevalently used paradigm in modeling semiconductor manufacturing processes, which as a neuron activation function typically employs a bipolar or unipolar sigmoid function in either hidden and output layers. In this study, applicability of another linear function as a neuron activation function is investigated. The linear function was operated in combination with other sigmoid functions. Comparison revealed that a particular combination, the bipolar sigmoid function in hidden layer and the linear function in output layer, is found to be the best combination that yields the highest prediction accuracy. For BPNN with this combination, predictive performance once again optimized by incrementally adjusting the gradients respective to each function. A total of 121 combinations of gradients were examined and out of them one optimal set was determined. Predictive performance of the corresponding model were compared to non-optimized, revealing that optimized models are more accurate over non-optimized counterparts by an improvement of more than 30%. This demonstrates that the proposed gradient-optimized teaming for BPNN with a linear function in output layer is an effective means to construct plasma models. The plasma modeled is a hemispherical inductively coupled plasma, which was characterized by a 24 full factorial design. To validate models, another eight experiments were conducted. process variables that were varied in the design include source polver, pressure, position of chuck holder and chroline flow rate. Plasma attributes measured using Langmuir probe are electron density, electron temperature, and plasma potential.

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수입 의류 제품의 에코라벨 인증마크 부착 여부, 제품군, 원산지 국가가 소비자의 신체적 위험지각, 제품에 대한 태도 및 구매의도에 미치는 영향 (Effects of Imported Fashion Products' Use of an Ecolabel, Product Category, and Country of Origin on Consumers' Perceived Physical Risk, Attitude Towards the Products, and Purchase Intention)

  • 유희정;심수인
    • 한국의류학회지
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    • 제44권1호
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    • pp.33-52
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    • 2020
  • Some consumers question the safety of imported fashion products. We examine the effects of the use of an ecolabel, product category, and country of origin on consumer responses such as perceived physical risk, attitude towards a product, subjective norm, and intention to purchase imported fashion products. A sample of 508 adults in their 30s to 40s participated in online survey experiments. The survey experiments used 2 (the use of the ecolabel vs no label) × 4 (country of origin: China, Dominican Republic, Norway, and the United States) between-subjects and 4 (product category: men/women's wear, children's wear, underwear, and accessories) within-sub-jects factorial design. A total of 32 product-catalog images (stimuli) and eight versions of the questionnaire were developed. The use of the ecolabel is identified as having a significantly lower perceived physical risk than the no-label. The consumers' perceived physical risk also differs depending on product category and country of origin. Consumers perceive a higher physical risk about children's wear and underwear than other product categories as well as fashion products sourced from developing countries than from developed countries. The reduction of physical risk is found to facilitate consumers' purchase decision-making process.

사각형 여과 집진기 충격기류 탈진시스템의 기초 연구 (The Fundamental Study on Pulse Jet Cleaning of Rectangular Bag-Filter System)

  • 박승욱;김태형;양준호;이효우;하현철;정재훈
    • 한국산업보건학회지
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    • 제18권2호
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    • pp.149-160
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    • 2008
  • Bag-filter system has been widely used in industrial field to remove the particulate matters from the exhaust gas. The cylindrical type of bag-filter has been generally used. But it has many shortcomings. The reattachment of separated particles on the surface of bags could result in high pressure drop of bag-filter system and subsequent decrease of air flow rate since the cylindrical type bag-filter system should have the upward flow pattern. In addition, the supply of very high pressure pulse air jet to remove particulate matters on the surface of filter could result in a frequent rupture of bags. To overcome these shortcomings of the cylindrical type, the rectangular type was developed in the developed countries and imported to Korea. But, there was not many design data available to understand the mechanisms. Thus, the fundamental experiments were conducted in this study to get some ideas about the pulse jet cleaning of rectangular type bag filter system. The experimental factors are as follows; pulse distance, pulse duration, pulse interval, pulse pressure and pulse nozzle type. Experiments followed the factorial design method. With the shorter pulse distance, the distribution of pressure drops was relatively not uniform while the particulate removal efficiency was higher. With the longer duration of pulsing and the more number of pulse nozzle, the removal efficiency was higher and the pressure drop distribution was more uniform.

Statistical Qualitative Analysis on Chemical Mechanical Polishing Process and Equipment Characterization

  • Hong, Sang-Jeen;Hwang, Jong-Ha;Seo, Dong-Sun
    • Transactions on Electrical and Electronic Materials
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    • 제12권2호
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    • pp.56-59
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    • 2011
  • The characterization of the chemical mechanical polishing (CMP) process for undensified phophosilicate glass (PSG) film is reported using design of experiments (DOE). DOE has been used by experimenters to understand the relationship between the input variables and responses of interest in a simple and efficient way, and it typically is beneficial for determining the appropriatesize of experiments with multiple process variables and making statistical inferences for the responses of interest. The equipment controllable parameters used to operate the machine consist of the down force of the wafer carrier, pressure on the back side wafer, table and spindle speeds (SS), slurry flow (SF) rate, pad condition, etc. None of these are independent ofeach other and, thus, the interaction between the parameters also needs to be understoodfor improved process characterization in CMP. In this study, we selected the five controllable equipment parameters the most recommendedby process engineers, viz. the down force (DF), back pressure (BP), table speed (TS), SS, and SF, for the characterization of the CMP process with respect to the material removal rate and film uniformity in percentage terms. The polished material is undensified PSG which is widely used for the plananization of multi-layered metal interconnects. By statistical modeling and the analysis of the metrology data acquired from a series of $2^{5-1}$ fractional factorial designs with two center points, we showed that the DF, BP and TS have the greatest effect on both the removal rate and film uniformity, as expected. It is revealed that the film uniformity of the polished PSG film contains two and three-way interactions. Therefore, one can easily infer that process control based on a better understanding of the process is the key to success in current semiconductor manufacturing, in which the size of the wafer is approaching 300 mm and is scheduled to continuously increase up to 450 mm in or slightly after 2012.

Actinobacillus succinogenes의 혐기성배양에 의해 생합성 되는 숙신산의 생산성 향상을 위한 통계적 생산배지 최적화 (Statistical Optimization of Production Medium for Enhanced Production of Succinic Acid Produced by Anaerobic Fermentations of Actinobacillus succinogenes)

  • 박상민;전계택
    • KSBB Journal
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    • 제29권3호
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    • pp.165-178
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    • 2014
  • Statistical medium optimization has been carried out for the production of succinic acid in anaerobic fermentations of Actinobacillus succinogenes. Succinic acid utilized as a precursor of many industrially important chemicals is a fourcarbon dicarboxylic acid, biosynthesized as one of the fermentation products of anaerobic metabolism by A. succinogenes. Through OFAT (one factor at a time) experiments, corn steep liquor (CSL), a very cheap agricultural byproduct, was found to have significant effects on enhanced production of succinic acid, when supplemented along with yeast extract. Hence, using these factors including glucose as a carbon/energy source, interactive effects were investigated through $2^n$ full factorial design (FFD) experiments, showing that the concentration of each component (i.e., glucose, yeast extract and CSL) should be higher. Further statistical experiments were conducted along the steepest ascent path, followed by response surface method (RSM) in order to find out optimal concentrations of each constituent. Consequently, optimized concentrations of glucose, yeast extract and CSL were observed to be 180 g/L, 15.08 g/L and 20.75 g/L respectively (10 g/L of $NaHCO_3$ and 100 g/L of $MgCO_3$ to be supplemented as bicarbonate suppliers), with the estimated production level of succinic acid to be 92.9 g/L (about 3.5 fold higher productivity as compared to the initial medium). Notably, the RSM-estimated production level was almost similar to the amount of succinic acid (92.9 g/L vs. 89.1 g/L) produced through the actual fermentation process performed using the statistically optimized production medium.

합성곱 신경망에서 이미지 분류를 위한 하이퍼파라미터 최적화 (Hyperparameter Optimization for Image Classification in Convolutional Neural Network)

  • 이재은;김영봉;김종남
    • 융합신호처리학회논문지
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    • 제21권3호
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    • pp.148-153
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    • 2020
  • 합성곱 신경망 모형에서 높은 정확도를 얻기 위해서는 최적의 하이퍼파라미터를 설정하는 작업이 필요하다. 하지만 높은 성능을 낼 수 있는 하이퍼파라미터 값이 정확히 알려진 바가 없으며, 자료마다 최적의 하이퍼파라미터 값이 달라질 수 있기 때문에 매번 실험을 통해서 찾아야만 한다. 또한, 하이퍼파라미터 값들의 범위가 넓고 조합 수가 많기 때문에 시간과 계산량을 줄이기 위해서는 최적값을 찾기 위한 실험 계획을 먼저 한 후에 탐색을 하는 것이 필요하다. 그러나 아직까지 합성곱 신경망 모형에서 하이퍼파라미터 최적화를 위하여 실험계획법을 이용한 연구 결과가 보고되지 않았다. 본 논문에서는 이미지 분류 문제에서 통계방법 중 하나인 실험계획법의 요인배치법을 이용하여 실험 계획을 하고 합성곱 신경망 분석을 한 후에, 높은 성능을 갖는 값을 중심으로 그리드 탐색을 하여 최적의 하이퍼파라미터를 찾는 방법을 제안한다. 실험 계획을 통하여 각 하이퍼파라미터들의 탐색 범위를 줄인 후에 그리드 탐색을 함으로써 효율적으로 연산량을 줄이고 정확도를 높힐 수 있음을 보였다. 또한 실험 결과에서 모형 성능에 가장 큰 영향을 주는 하이퍼파라미터가 학습률이라는 것을 확인할 수 있었다.

중심합성계획법에 의한 남부 조생벼 재배요인의 최적조건 구명 (Optimization of Cultivational Conditions of Rice(Oryza sativa L.) by a Central Composite Design Applied to an Early Cultivar in Southern Region)

  • 손길만;김정교;최진용;이유식;박중양
    • 한국작물학회지
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    • 제34권1호
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    • pp.60-73
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    • 1989
  • 수도재배에 있어서 수량은 여러 가지 요인이 복합적으로 작용하여 나타난 반응의 산물이다. 수도의 적정재배조건을 구명하기 위하여 지금까지는 제한된 요인 및 수준에서 시험연구가 수행되어 왔는데, 처리요인수 및 각 요인당 처리수준이 증가될 경우 전체 처리수의 급증으로 시험수행이 어렵게 된다. 본 연구는 이를 극복하고자 조생량 벼 품종 '운봉벼'의 재식주수, 주당본수, 질소시비량, 이앙일, 육묘일수 등 5가지 계량적 재배요인의 최적조건을 구명하기 위한 시험을 수행하고 수량을 Box와 Wilson의 중심합성계획법에 따라 분석하였으며(시험 1), 같은 품종을 공시하여 실험 1과 같은 요인을 Finney의 부분실시법(FFD)과 비교함으로써(시험 2) CCD의 농사시험연구에의 활용가능성을 제시하고자 하였다. 1. 재배조건에 따른 수량반응 수량은 5요인중 4요인의 수준을 중심수준에서 통제하였을 때 각 요인별 최대수량은 중심수준(재식주수, 90수/3.3$m^2$ ; 주당본수, 5본 ; N시비량, 11kg/10a ; 이앙일, 6월 25일 ; 육묘일수, 35일) 부근이었고 각 요인이 양극단수준으로 갈수록 감수하였으며 5요인중 3요인을 중심수준에서 통제하고 난 뒤에 2요인들 간의 상호작용에 의한 수량은 가 수준의 중심부에서 최고치를 보였다. 전체 5개 요인의 상호작용에 의해 나타난 수량의 정상점은 안부점이었다. 2. 두 계획법의 비교 가. CCD에서 수량에 대한 각각의 정상점에서의 재배조건은, 재식주수 107주/3.3$m^2$, 주당본수 4본, 질소시비량 10kg/10a, 이앙일 6월 26일, 육묘일수 33일이었고, 정상점에서의 수량은 439kg/10a으로서 FFD에서의 그것들과 비슷하였다. 나. CCD에 의하면 요인수와 수준수가 많아도 처리조합수를 획기적으로 줄일 수 있었고, 실험재료의 절적, 작업시간의 단축 및 작업의 간편화를 가져왔다. 다. CCD(각 요인별 5수준)는 FFD(각 3수준)에 비하여 수준수가 많았지만 결과를 도해화하기에 편리하였다. 라. 양 계획법에 있어서 수량의 정상점이 안부점인 것으로 보아 요인의 설정시 각 요인 상호간의 이질성을 고려해야 하며, 처리요인의 지나친 증가도 억제되어야 할 것이다. 마. CCD는 극한수준($\pm$2, $\pm$2, $\pm$2, $\pm$2, $\pm$2)의 처리가 없기 때문에 각 요인의 극한수준의 실험영역에 대해서는 적은 정보를 얻었으나. FFD보다는 많은 유익한 정보를 획득할 수 있었다. 따라서, CCD는 획기적으로 처리수를 줄였어도 유익한 정보를 제공하는 것으로 보아, 농사시험연구에 효율적으로 활용할 수 있는 계획적으로 확인되었다.적으로 확인되었다.

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