• Title/Summary/Keyword: full factorial

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Effect of Circumferential Tool Path Control on Friction Stir Spot Welding of Al/Fe Dissimilar Metal Joint (툴 경로제어를 이용한 Al/Fe 이종금속 마찰교반점용접 공정특성 평가)

  • Yoon, Jin Young;Kim, Cheolhee;Rhee, Sehun
    • Journal of Welding and Joining
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    • v.34 no.3
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    • pp.6-11
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    • 2016
  • Joining Al/Fe dissimilar metals is becoming a subject of special interest in the assembly of automotive parts as a trade-off between the weight lightening and the cost reduction. Although various studies have been introduced to join Al alloy with the steel sheet by fusion welding, weak joint strength and galvanic corrosion still remained as problems to be solved. As a solid state welding, friction stir welding has been preferred to fusion welding processes in the dissimilar metal joints. This study investigated friction stir spot welding (FSSW) of Al alloy to the thin steel sheet with a thickness of 0.65 mm. The conventional FSSW is a stationary spot welding process but new approach adopted an additional circumferential movement in company with high speed tool rotation. A full factorial experimental design was implemented, and the main and interaction effects of parameters were analysed on the failure load in the tensile shear test. The direction and radius of rotation were statistically significant parameters and these two parameters affected the joint width and the shape of the hook.

Thin film solar cell efficiency improvement using the surface plasmon effect (표면 플라즈몬 효과를 이용한 박막형 태양전지 효율향상)

  • Byun, Soo-Hwan;Soh, Hyun-Jun;Yoo, Jeong-Hoon
    • Transactions of the Society of Information Storage Systems
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    • v.8 no.2
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    • pp.39-43
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    • 2012
  • In spite of many advantages, the practical application of the thin film solar cell is restricted due to its low efficiency compared with the bulk type solar cells. This study intends to adopt the surface plasmon effect using nano particles to solve the low efficiency problem in thin film solar cells. By inserting Ag nano-particles in the absorbing layer of a thin film solar cell, the poynting vector value of the absorbing layer is increased due to the strong energy field. Increasing the value may give thin film solar cells chance to absorb more energy from the incident beam so that the efficiency of the thin film solar cell can be improved. In this work, we have designed the optimal shape of Ag nano-particle in the absorbing laser of a basic type thin film solar cell using the finite element analysis commercial package COMSOL. Design parameters are set to the particle diameter and the distance between each Ag nano-particle and by changing those parameters using the full factorial design variable set-up, we can determine optimal design of Ag nano-particles for maximizing the poynting vector value in the absorbing layer.

NUMBER OF CYCLES IN EVOLUTIONARY OPERATION

  • Lim, Yong-B.;Park, Sung-H.
    • Journal of the Korean Statistical Society
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    • v.36 no.2
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    • pp.201-208
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    • 2007
  • Evolutionary operation (EVOP) proposed by Box (1957) is a method for continuous monitoring and improvement of a full-scale manufacturing process with the objective of moving the operating conditions toward the better ones. EVOP consists of systematically making small changes in the levels of the two or three process variables under consideration. Data are collected on the response variable at each point of two level factorial design with the center point and a cycle is said to have been completed. The cycles are replicated sequentially until the decision is made on whether further cycle of experiments is needed to conclude the significance of any of main effects or interaction effects or the curvature. In this paper, an improved flow chart of EVOP is proposed and how to determine the number of cycles is studied based on the size of type II error. In order to reject the alternative hypothesis of interests with more confidence and conclude that we believe in the null hypothesis of no effects, we propose a counter measure $p^*-value$ corresponding to the p-value. The relationship of $p^*-value$ to the probability of type II error ${\beta}$ under the alternative hypothesis of interests is analogous to that of p-value to the probability of type I error ${\alpha}$. Also the implementation of EVOP with a mixture experiment is discussed.

Random generator-controlled backpropagation neural network to predicting plasma process data

  • Kim, Sungmo;Kim, Sebum;Kim, Byungwhan
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.599-602
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    • 2003
  • A new technique is presented to construct predictive models of plasma etch processes. This was accomplished by combining a backpropagation neural network (BPNN) and a random generator (RC). The RG played a critical role to control neuron gradients in the hidden layer, The predictive model constructed in this way is referred to as a randomized BPNN (RG-BPNN). The proposed scheme was evaluated with a set of experimental plasma etch process data. The etch process was characterized by a 2$^3$ full factorial experiment. The etch responses modeled are 4, including aluminum (Al) etch rate, profile angle, Al selectivity, and do bias. Additional test data were prepared to evaluate model appropriateness. The performance of RC-BPNN was evaluated as a function of the number of hidden neurons and the range of gradient. for given range and hidden neurons, 100 sets of random neuron gradients were generated and among them one best set was selected for evaluation. Compared to the conventional BPNN, the proposed RC-BPNN demonstrated about 50% improvements in all comparisons. This illustrates that the RG-BPNN of multi-valued gradients is an effective way to considerably improve the predictive ability of current BPNN of single-valued gradient.

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Optimal Design of the Front Upright of Formula Race Car Using Taguchi's Orthogonal Array (다구찌 직교배열법을 이용한 포뮬러 레이스카 전륜 업라이트의 최적설계)

  • Jang, Woon Geun
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.1
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    • pp.112-118
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    • 2013
  • Formula race car is generally recognized as a vehicle which is optimally designed for on-road race track with the regulations of race host bodies. Especially, the uprights of suspension system decisively have effects on the performance of cornering and stability of race car's driving performance, which are very important factors in the design of race car. This paper is a study of optimal upright design of F1800 grade formula race car which are normally used in professional race circuit in Korea. To design optimally the front upright of F1800 formula race car, Taguchi's orthogonal array, which is known for more useful method than full factorial design experimental method in cost and time, is used with CAE method such as FEM analysis. And the result of this paper shows that Taguchi's orthogonal array employed for this optimal design is very useful for designing the front upright of race car by minimizing its weight as well as keeping its safety factor as enough as designer wants in the view of quality, cost and delivery at the early design step.

Effect of Process Parameters on the Hardness and Wear Rate of Thermal Sprayed Ni-based Coatings (니켈기 경질 용사코팅의 경도 및 마모율에 미치는 공정조건의 영향)

  • Kim, K.T.;Kim, J.D.;Kim, Y.S.
    • Journal of Power System Engineering
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    • v.15 no.1
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    • pp.51-56
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    • 2011
  • The various process parameters of thermal spray process affects on quality of Ni-based coatings. Thus, there is need to analyze the effect of process parameters on quality of Ni-based coatings. In this paper, the effects of process parameters on hardness and wear rate of Ni-based coatings were investigated using 4 design of experiments. First, the Ni-based coatings were fabricated according to $L_9(3^4)$ orthogonal array. The hardness tests and the wear tests were performed on the Ni-based coatings. The analysis of variance for the hardness and wear rate were carried out. As a results, the acetylene gas flow and the powder feed rate were identified as main factors effected on the hardness and the oxygen gas flow and the acetylene gas flow were identified as main factors effected on the wear rate. The full factorial experiments design with different levels was applied for investigation of effect of these main factors.

Determination of the Optimal Configuration of Operation Policies in an Integrated-Automated Manufacturing System Using the Taguchi Method and Simulation Experiments (다구치방법과 시뮬레이션을 이용한 통합된 자동생산시스템의 최적운영방안의 결정)

  • Lim, Joon-Mook;Kim, Kil-Soo;Sung, Ki-Seok
    • IE interfaces
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    • v.11 no.3
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    • pp.23-40
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    • 1998
  • In this paper, a method to determine the optimal configuration of operating policies in an integrated-automated manufacturing system using the Taguchi method and computer simulation experiments is presented. An integrated-automated manufacturing system called direct-input-output manufacturing system(DIOMS) is described. We only consider the operational aspect of the DIOMS. Four operating policies including input sequencing control, dispatching rule for the storage/retrieval(S/R) machine, machine center-based part type selection rule, and storage assignment policy are treated as design factors. The number of machine centers, the number of part types, demand rate, processing time and the rate of each part type, vertical and horizontal speed of the S/R machine, and the size of a local buffer in the machine centers are considered as noise factors in generating various manufacturing system environment. For the performance characteristics, mean flow time and throughput are adopted. A robust design experiment with inner and outer orthogonal arrays are conducted by computer simulation, and an optimal configuration of operating policies is presented which consists of a combination of the level of each design factor. The validity of the optimal configurations is investigated by comparing their signal-to-noise ratios with those obtained with full factorial designs.

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Prediction of Blank Thickness Variation in a Deep Drawing Process Using Deep Neural Network (심층 신경망 기반 딥 드로잉 공정 블랭크 두께 변화율 예측)

  • Park, K.T.;Park, J.W.;Kwak, M.J.;Kang, B.S.
    • Transactions of Materials Processing
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    • v.29 no.2
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    • pp.89-96
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    • 2020
  • The finite element method has been widely applied in the sheet metal forming process. However, the finite element method is computationally expensive and time consuming. In order to tackle this problem, surrogate modeling methods have been proposed. An artificial neural network (ANN) is one such surrogate model and has been well studied over the past decades. However, when it comes to ANN with two or more layers, so called deep neural networks (DNN), there is distinct a lack of research. We chose to use DNNs our surrogate model to predict the behavior of sheet metal in the deep drawing process. Thickness variation is selected as an output of the DNN in order to evaluate workpiece feasibility. Input variables of the DNN are radius of die, die corner and blank holder force. Finite element analysis was conducted to obtain data for surrogate model construction and testing. Sampling points were determined by full factorial, latin hyper cube and monte carlo methods. We investigated the performance of the DNN according to its structure, number of nodes and number of layers, then it was compared with a radial basis function surrogate model using various sampling methods and numbers. The results show that our DNN could be used as an efficient surrogate model for the deep drawing process.

Modeling of plamsa etch process using a radial basis function network (레이디얼 베이시스 함수망을 이용한 플라즈마 식각공정 모델링)

  • Park, Kyoung-Young;Kim, Byung-Whan;Lee, Byung-Teak
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2004.07b
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    • pp.1129-1133
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    • 2004
  • 반도체공정 최적화에 소요되는 시간과 경비를 줄이기 위해 신경망 모델이 개발되고 있다. 주로 역전파 신경망을 이용하여 모델이 개발되고 있으며, 본 연구에서는 Radial Basis Function Network (RBFN)을 이용하여 플라즈마 식각공정 모델을 개발한다. 실험데이터는 유도결합형 플라즈마를 이용한 Silicon Carbide 박막의 식각공정으로부터 수집되었다. 모델개발을 위해 $2^4$ 전인자 (full factorial) 실험계획법이 적용되었으며, 모델에 이용된 식각응답은 식각률과 atomic force microscopy로 측정한 식각표면 거칠기이다. 모델검증을 위해 추가적으로 16번의 실험을 수행하였다. RBFN의 예측성능은 세 학습인자, 즉 뉴런수, width, 초기 웨이트 분포 (initial weight distribution-IWD) 크기에 의해 결정된다. 본 연구에서는 각 학습인자의 영향을 최적화하였으며, IWD의 불규칙성을 고려하여 주어진 학습인자에 대해서 100개의 모델을 발생하고, 이중 최소의 IWD를 갖는 모델을 선택하였다. 최적화한 식각률과 표면거칠기 모델의 RMSE는 각기 26 nm/min과 0.103 nm이었다. 통계적인 회귀모델과 비교하여, 식각률과 표면거칠기 모델은 각기 52%와 24%의 향상된 예측정확도를 보였다. 이로써 RBFN이 플라즈마 공정을 효과적으로 모델링 할 수 있음을 확인하였다.

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Binary Mixture Toxicity of AROCLOR 1248, Oleic Acid, and Elemental Sulfur to Vibrio fischeri Luminescence

  • Kalciene, Virginija;Dabkeviciene, Daiva;Cetkauskaite, Anolda
    • Journal of Environmental Science International
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    • v.24 no.11
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    • pp.1541-1546
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    • 2015
  • The objective of this research was to evaluate the toxicity of the industial xenobiotic Aroclor 1248 (A) and natural origin substances~elemental sulfur (S80) and oleic acid (OA) and their binary mixtures to V. fischeri bioluminescence during the prolonged exposure time (up to 60 min). The bioluminescence quenching test was used to determine the toxic effects. Full factorial experiment design and multiple regression analysis and the comparison of binary mixture effect with the sum of effects of individual chemicals were used for the evaluation of combined effects of toxicants. The analysis of general trend of mixture toxicity to bioluminescence showed that mixture toxic effects were reversible up to 60 min. Data analysis revealed different joint effects, which were depended on mixture composition. S80 enhanced toxic effect of A and acted additively with synergistic interaction. Hydrophobic OA in mixture with A acted antagonistically and in mixture with sulfur caused an additive effect with antagonistic component of interaction. It was concluded that low concentrations of natural toxic substances present in environmental samples as mixtures of chemicals can define the toxicodynamic character of industrial xenobiotics.