• Design & Manufacturing
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• 제2권1호
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• pp.11-14
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• 2008

we can save a development cost and time as computer was used in tool and die design of car fields in die manufacture process. Dimension accuracy errors such as springback, springgo, overcrown and twist were reduced product accuracy and caused trouble to assembly each parts of car. In this paper, CADCEUS was used to modify and optimize results of deflection for a tail gate panel of car parts in order to reduce dimension accuracy errors by springback in sheet metal forming. As CADCEUS was used to apply for a tail gate panel, the time for quality to improve was reduced to 30%.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 추계학술대회논문집
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• pp.338-341
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• 2004

The dimension of forged part is different with the die dimension by the various effects, such as, elastic deformation and thermal effect. And, the difference amounts are not same according to the forging conditions, for example, forging mode, flow stress, etc. Therefore, the use of FEA is effective to predict and update the required die dimension. However, the variables for FE simulation are also as many as variables in the experiment. The variables give very much effect to the accuracy of FE results. At first, the material model is very deeply affected to the estimated dimension of forged part. And the considering of loading and ejecting stages is also important to increase the dimensional accuracy. The experiment and FEA are performed to investigate the dimensional changes and accuracy in cold forging. Two types of upsetting are used to survey the effects of forging mode and stages.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2003년도 추계학술대회논문집
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• pp.34-38
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• 2003

In metal working, cold forging that has profit to satisfy dimension accuracy is using in various manufacturing products. Recently, most of the interest thing is precision forging of gear. Gear forging product is more strength than broaching gear, and it has many advantages with reduction of factory expenses. The reason of difficulty to improve accuracy of gear dimension compare to another products is the dimension accuracy is very high, approximately 10$\mu\textrm{m}$, and because die of involute teeth and elastic strain of forged tool differ from standard curve. This paper represent quantitative analysis of die and teeth of forged tool, namely difference of curves, with experiments and analyze the factor of dimension gap, finally, will design compensated involute curve.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2003년도 춘계학술대회논문집
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• pp.44-48
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• 2003

In metal working, cold forging that has profit to satisfy dimension accuracy is using in various manufacturing products. Recently, most of the interest thing is precision forging of gear, Gear forging product is more strength than broaching gear, and it has many advantages with reduction of factory expenses. The reason of difficulty to improve accuracy of gear dimension compare to another products is the dimension accuracy is very high, approximately 10$\mu\textrm{m}$, and because die of involute teeth and elastic strain of forged tool differ from standard curve. This paper represent quantitative analysis of die and teeth of forged tool, namely difference of curves, with experiments and analyze the factor of dimension gap, finally, will design compensated involute curve.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 춘계학술대회 논문집
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• pp.129-134
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• 2009

The dimension of forged part is different from that of die. Therefore, a more precise die dimension is necessarys to produce the precise part, considering the dimensional changes from forging die to final part. In this paper, both experimental and FEM analysis are performed to investigate the effect of several features including die dimension at each forging step and heat-treatment on final part accuracy in the closed-die upsetting. The dimension of forged part is checked at each stage as machined die, cold forged, and post-heat-treatment steps. The elastic characteristics and thermal influences on forging stage are analyzed numerically by the DEFORM-$2D^{TM}$. The effect of residual stress after heat-treatment on forged part could be considered successfully by using DEFOAM-$HT^{TM}$.

• 한국농림기상학회지
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• 제14권4호
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• pp.269-276
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• 2012

작물모형 평가에 사용되거나 사용할 수 있는 9가지 지표를 소개하였으며 이들의 특징은 다음과 같다. efficiency of model (EF)와 index of agreement (d)은 dimension이 없고 관측수(n)에 의존적이지 않았으며, dimension에 대해서만 자유로운 것은 relative root mean square error (RRMSE), bias factor (Bf)와 accuracy factor (Af)이다. Root mean sqruar, mean error, mean absolute error들은 관측수와 dimension에 영향을 받기 때문에 판단 시 주의가 필요하다. 따라서 이들의 특징을 파악하여 목적에 맞게 모형의 성능을 파악하여야 한다.

• 한국음향학회지
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• 제41권5호
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• pp.492-499
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• 2022

본 연구에서는 진동 신호의 차원 감소가 선박 엔진의 고장진단에 미치는 영향을 실험적으로 분석한 결과를 제시한다. 주성분 분석을 이용하여 513차원의 진동 신호를 1 ~ 15차원의 저차원 신호로 변환하여 차원 변화에 따른 고장진단 정확도의 변화를 관찰하였다. 실제 규모의 선박용 발전기 디젤 엔진에서 측정된 진동 신호를 사용하고, integrated gradients와 feature permutation 기법의 두 가지 변수 중요도 분석 알고리즘을 사용하여 차원 축소 신호의 기여도를 정량적으로 평가하였다. 실험 데이터 분석 결과, 사용하는 차원의 수가 증가할수록 결함 진단의 정확도가 향상되는 것으로 나타났다. 차원이 10 이상에 다다르면 거의 모든 고장상태가 정확하게 분류되었으며, 이는 고장진단 정확도를 저하시키지 않으면서도 진동 신호의 차원수를 크게 줄일 수 있음을 보여준다. 변수 중요도 분석에서도 차원 축소 주성분이 기존 통계적 특성보다 더 높은 기여도를 보였으며, 차원 축소된 진동 스펙트럼이 고장진단에 효과적으로 사용될 수 있음을 확인하였다.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.80-87
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• 2024

This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2003년도 The 8th Asian Symposium on Precision Forging ASPF
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• pp.26-30
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• 2003

Since the dimension of cold forged part is larger than the cavity size of forging die, the difference results from the various features, such as, the elastic characteristics of die and workpiece, thermal influences, and machine-elasticity. All of these factors should be considered to get more accurate prediction of the dimension of forged part. In this paper, severe FE techniques are proposed to improve the prediction accuracy of dimension for cold forged part. To validate the importance of the above mentioned factors, and the estimated results are compared with the experimental results. The used model is a closed die upsetting of cylindrical billet. The calculated dimensions are well coincided with .the measured values based on the proposed techniques. The proposed techniques have put two simple but important points into Fe simulation. One is the separation of forging stages into 3 steps, from a loading through punch retraction to ejecting stage. The other is the dimensional change, according to the temperature changes due to the deformation. The FE analysis could predict the dimension of cold forged part within the $10{\mu}m$, based on the more realistic consideration.