• Title/Summary/Keyword: Processing variables

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On the Efficiency Comparison of Dynamic Program Slicing Algorithm using Multiple Criteria Variables (다중 기준변수를 사용한 동적 프로그램 슬라이싱 알고리즘의 효율성 비교)

  • Park, Sun-Hyeong;Park, Man-Gon
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.9
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    • pp.2384-2392
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    • 1999
  • Software engineers are used to analyse the error behavior of computer programs using test cases which are collected for the testing phase when software errors are detected. In actual software testing and debugging, it is important to adopt dynamic slicing technique which is concerned on all the statements to be affected by the variables of current inputs and to use technique of its implementations. The traditional dynamic slicing has focused on the single slicing criterion algorithm. It has been thought that it is needed to develope and implement algorithm for used multiple criteria variables program slicing, which finds every slicing criterion variable where it is used multiple criteria variables. In this paper, we propose an efficient algorithm to make dynamic program slices when it has used multiple criteria variables. The results of the implementation are presented by the making table on execution history and the dynamic dependence graph. Also we can find that the proposed dynamic program slicing approach using multiple criteria variables is more efficient than the traditional single case algorithm on the practical testing environment.

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Analysis of Research Trends on Electrochemical-Mechanical Planarization (전기화학-기계적 평탄화에 관한 연구 동향 분석)

  • Lee, Hyunseop;Kim, Jihun;Park, Seongmin;Chu, Dongyeop
    • Tribology and Lubricants
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    • v.37 no.6
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    • pp.213-223
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    • 2021
  • Electrochemical mechanical planarization (ECMP) was developed to overcome the shortcomings of conventional chemical mechanical planarization (CMP). Because ECMP technology utilizes electrochemical reactions, it can have a higher efficiency than CMP even under low pressure conditions. Therefore, there is an advantage in that it is possible to reduce dicing and erosions, which are physical defects in semiconductor CMP. This paper summarizes the papers on ECMP published from 2003 to 2021 and analyzes research trends in ECMP technology. First, the material removal mechanisms and the configuration of the ECMP machine are dealt with, and then ECMP research trends are reviewed. For ECMP research trends, electrolyte, processing variables and pads, tribology, modeling, and application studies are investigated. In the past, research on ECMP was focused on basic research for the development of electrolytes, but it has recently developed into research on tribology and process variables and on new processing systems and applications. However, there is still a need to increase the processing efficiency, and to this end, the development of a hybrid ECMP processing method using another energy source is required. In addition, ECMP systems that can respond to the developing metal 3D printing technology must be researched, and ECMP equipment technology using CNC and robot technology must be developed.

A STUDY OF ESTIMATION GROUND SURFACE TEMPERATURE BY TIME-SHIFT PROCESSING

  • Yano, Koji;KAJIWARA, Koji;HONDA, Yoshiaki;Moriyama, Masao
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.798-800
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    • 2003
  • The time shift processing of ground measured surface temperature with the meteorological variables has no evaluated function. We introduce new evaluating function. To use this evaluating function, the algorithm of time-shift processing will be able to be reliable and get error-bar for all moving measured point's data. We will finally obtain the area averaged surface temperature by land observation.

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A study on the prediction of optimized injection molding conditions and the feature selection using the Artificial Neural Network(ANN) (인공신경망을 통한 사출 성형조건의 최적화 예측 및 특성 선택에 관한 연구)

  • Yang, Dong-Cheol;Kim, Jong-Sun
    • Design & Manufacturing
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    • v.16 no.3
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    • pp.50-57
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    • 2022
  • The qualities of the products produced by injection molding are strongly influenced by the process variables of the injection molding machine set by the engineer. It is very difficult to predict the qualities of the injection molded product considering the stochastic nature of the manufacturing process, since the processing conditions have a complex impact on the quality of the injection molded product. It is recognized that the artificial neural network(ANN) is capable of mapping the intricate relationship between the input and output variables very accurately, therefore, many studies are being conducted to predict the relationship between the results of the product and the process variables using ANN. However in the condition of a small number of data sets, the predicting performance and robustness of the ANN model could be reduced due to too many input variables. In the present study, the ANN model that predicts the length of the injection molded product for multiple combinations of process variables was developed. And the accuracy of each ANN model was compared for 8 process variables and 4 important process inputs that were determined by the feature selection. Based on the comparison, it was verified that the performance of the ANN model increased when only 4 important variables were applied.

Optimal Reheating Condition of Semi-solid Material in Semi-solid Forging by Neural Network

  • Park, Jae-Chan;Kim, Young-Ho;Park, Joon-Hong
    • International Journal of Precision Engineering and Manufacturing
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    • v.4 no.2
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    • pp.49-56
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    • 2003
  • As semi-solid forging (SSF) is compared with conventional casting such as gravity die-casting and squeeze casting, the product without inner defects can be obtained from semi-solid forming and globular microstructure as well. Generally, SSF consists of reheating, forging, and ejecting processes. In the reheating process, the materials are heated up to the temperature between the solidus and liquidus line at which the materials exists in the form of liquid-solid mixture. The process variables such as reheating time, reheating temperature, reheating holding time, and induction heating power has large effect on the quality of the reheated billets. It is difficult to consider all the variables at the same time for predicting the quality. In this paper, Taguchi method, regression analysis and neural network were applied to analyze the relationship between processing conditions and solid fraction. A356 alloy was used for the present study, and the learning data were extracted from the reheating experiments. Results by neural network were in good agreement with those by experiment. Polynominal regression analysis was formulated using the test data from neural network. Optimum processing condition was calculated to minimize the grain size and solid fraction standard deviation or to maximize the specimen temperature average. Discussion is given about reheating process of row material and results are presented with regard to accurate process variables fur proper solid fraction, specimen temperature and grain size.

Spatial Interpolation of Meteorologic Variables in Vietnam using the Kriging Method

  • Nguyen, Xuan Thanh;Nguyen, Ba Tung;Do, Khac Phong;Bui, Quang Hung;Nguyen, Thi Nhat Thanh;Vuong, Van Quynh;Le, Thanh Ha
    • Journal of Information Processing Systems
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    • v.11 no.1
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    • pp.134-147
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    • 2015
  • This paper presents the applications of Kriging spatial interpolation methods for meteorologic variables, including temperature and relative humidity, in regions of Vietnam. Three types of interpolation methods are used, which are as follows: Ordinary Kriging, Universal Kriging, and Universal Kriging plus Digital Elevation model correction. The input meteorologic data was collected from 98 ground weather stations throughout Vietnam and the outputs were interpolated temperature and relative humidity gridded fields, along with their error maps. The experimental results showed that Universal Kriging plus the digital elevation model correction method outperformed the two other methods when applied to temperature. The interpolation effectiveness of Ordinary Kriging and Universal Kriging were almost the same when applied to both temperature and relative humidity.

Process Design for Large-Scale Ring-Rolling of Ti-6Al-4V Alloy (Ti-6Al-4V 합금의 대형 링 압연공정설계)

  • Yeom, J.T.;Kim, J.H.;Lee, D.G.;Park, N.K.;Choi, S.S.;Lee, C.S.
    • Transactions of Materials Processing
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    • v.16 no.3 s.93
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    • pp.172-177
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    • 2007
  • The process design for large-scale ring rolling of Ti-6Al-4V alloy was performed by calculation method, processing map approach and FEM simulation. The ring rolling design includes geometry design and optimization of process variables. The calculation method was used to make geometry design such as initial billet and blank sizes, and final rolled ring shape. A commercial FEM code, SHAPE-RR was used to simulate the effect of process variables in ring rolling on the distribution of the internal state variables such as strain, strain rate and temperature. In order to predict the forming defects during ring rolling and the formation of over-heating above $\beta$-transus temperature due to deformation heating, the process-map approach based on Ziegler's instability criterion was used with FEM simulation. Finally, an optimum process design to obtain sound Ti-6Al-4V rings without forming defects was suggested through combined approach of Ziegler's instability map and FEM simulation results.