• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1166-1172
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• 2003

The extremely strong competition among the world automobile industries has introduced the concept of PLM in the total production activities, one of whose major components is VM(Virtual Manufacturing). If the production lines are equipped with robots, the application of OLP in the virtual space is fully mature. However, in the point of the investment's and the maintenance's view, there are always some activities, which can not be automated: for example, typically the manual welding for prefixing in the automobile body shop and the material loading. Process planning for these activities, therefore, are decided mainly by experiences, which caused many repeated rework of the processes and the inconvenience of the workers, and resulted consequently in the reduction of the productivity and the safety of the workers. In this paper, the optimal dimension of the welding gun and its handle position and the optimal working path is simulated and decided by use of DELIMN/IGRIP and DELMIA/Ergo and the working area modelized in the virtual workcell of DELMIA.

• Journal of The Korean Astronomical Society
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• v.37 no.2
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• pp.79-85
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• 2004

We developed an algorithm to identify and determine periods of variable sources. With its robustness and high speed, it is expected to become an useful tool for surveys with large volume of data. This new scheme consists of an initial coarse. process of finding several candidate periods followed by a secondary process of much finer period search. With this multi-step approach, best candidates among statistically possible periods are produced without human supervision and also without any prior assumption on the nature of the variable star in question. We tested our algorithm with 381 stars taken from the ASAS survey and the result is encouraging. In about $76\%$ cases, our results are nearly identical as their published periods. Our algorithm failed to provide convincing periods for only about $10\%$ cases. For the remaining $14\%$, our results significantly differ from their periods. We show that, in many of these cases, our periods are superior and much closer to the true periods. However, the existence of failures, and also periods sometimes worse than manually controlled results, indicates that this algorithm needs further improvement. Nevertheless, the present experiment shows that this is a positive step toward a fully automated period analysis for future variability surveys.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.128-133
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• 1999

In recent years, LSI devices have become more powerful and lower-priced, caused by a development of various wafer materials and an increase in the diameter of wafers. On the other hand, these have created some serious problems in manufacturing of wafers because materials used as semiconductor substrate are very brittle. In view of this fact, there are some trials to apply shear-mode(or ductile-mode) grinding for efficient manufacturing of semiconductor wafers instead of conventional lapping process. In fact grinding process that has not only more excellent degree of accuracy but also more adaptable to fully automated manufacturing than lapping, is already used in Si machining field. This paper described the elementary studies to establish the grinding technology of wafers. First, we investigated the variation of grinding force and the transition of grinding mode as various grinding conditions. Then, it was inspected that the change of grinding force affected the integrity such as the topography and the roughness of ground surfaces, and led to the chemical defects generation and distribution in damaged layer. The degree of defects was estimated by FT-IR(Fourier Transformed Infrared) Spectroscopy and Auger Electron Spectroscopy

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.7
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• pp.56-62
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• 2019

The high-precision laser scriber carries out scribing alumina ceramic substrates for manufacturing ultra-small chip resistors. The ceramic substrates are loaded, aligned, scribed, transferred, and unloaded. The entire process is fully automated, thereby minimizing the scribing cycle time of the ceramic substrates and improving the throughput. The scriber consists of the laser optical system, pick-up module of ceramic substrates, pre-alignment module, TH axis drive work table, automation module for substrate loading / unloading, and high-speed scribing control S/W. The loader / unloader unit, which has the greatest influence on the scribing cycle time of the substrates, carries the substrates to the work table that carries out the cutting line work by driving the X and Y axes as well as by adsorbing the ceramic substrates. The loader / unloader unit consists of the magazine up / down part, X-axis drive part for conveying the substrates to the left and right direction, and the vision part for detecting the edge of the substrate for the primary pre-alignment of the substrates. In this paper, the laser scribing machining simulation is performed by applying the instrument mechanism of each component module. Through this study, the scribing machining process is first verified by analyzing the process operation and work area of each module in advance. In addition, the scribing machining process is optimized by comparing and analyzing the scribing cycle time of one ceramic substrate according to the alignment stage module speed.

• Journal of Welding and Joining
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• v.35 no.2
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• pp.43-51
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• 2017

The automatic welding systems, have received much attention in recent years, because they are highly suitable not only to increase the quality and productivity, but also to decrease manufacturing time and cost for a given product. Automatic welding work in semiconductor or space industry to be carried out in pipe line and butt joint mostly and plasma arc welding(PAW) is actively applied. To get the desired quality welds in automated welding system is challenging, a mathematical model is needed that has complete control over the relevant process parameters in order to obtain the required mechanical properties. However, In various industries the welding process mathematical model is not fully formulated for the process parameter and on the welding conditions, therefore only partial variables can be predicted. Therefore, this paper investigates the interaction between the welding parameters and mechanical properties for predicting the weld bead geometry by analyzing the S/N ratio.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.47-53
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• 2005

The efficiency of fabrication (fab) operation is one of the key factors in order for a semiconductor manufacturing company to stay competitive. Optimization of manpower and forecasting manpower needs in a modern fab is an essential part of the future strategic planing and a very important to the operational efficiency. As the semiconductor manufacturing technology has entered the 8-inch wafer era, the complexity of fab operation increases with the increase of wafer size. The wafer handling method has evolved from manual mode in 6-inch wafer fab to semi-automated or fully automated factory in 8-inch and 12-inch wafer fab. The distribution of manpower requirement in each specialty varied as the trend of fab operation goes for downsizing manpower with automation and outsourcing maintenance work. This paper is to study the specialty distribution of manpower from the requirement in a typical 6-inch, 8-inch to 12-inch wafer fab. The human resource planning in today’s fab operation shall consider many factors, which include the stability of technical talents. This empirical study mainly focuses on the human resource planning, the manpower distribution of specialty structure and the forecast model of internal demand/supply in current semiconductor manufacturing company. Considering the market fluctuation with the demand of varied products and the advance in process technology, the study is to design a headcount forecast model based on current manpower planning for direct labour (DL) and indirect labour (IDL) in Taiwan’s fab. The model can be used to forecast the future manpower requirement on each specialty for the strategic planning of human resource to serve the development of the industry.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.7-15
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• 2020

Recently, the fourth industrial revolution has been presented as a new paradigm and additive manufacturing (AM) has become one of the most important topics. For this reason, process monitoring for each cross-sectional layer of additive metal manufacturing is important. Particularly, deep learning can train a machine to analyze, optimize, and repair defects. In this paper, image classification is proposed by learning images of defects in the metal cross sections using the convolution neural network (CNN) image labeling algorithm. Defects were classified into three categories: crack, porosity, and hole. To overcome a lack-of-data problem, the amount of learning data was augmented using a data augmentation algorithm. This augmentation algorithm can transform an image to 180 images, increasing the learning accuracy. The number of training and validation images was 25,920 (80 %) and 6,480 (20 %), respectively. An optimized case with a combination of fully connected layers, an optimizer, and a loss function, showed that the model accuracy was 99.7 % and had a success rate of 97.8 % for 180 test images. In conclusion, image labeling was successfully performed and it is expected to be applied to automated AM process inspection and repair systems in the future.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.1
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• pp.18-23
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• 2022

Electrohydrodynamic jet (e-jet) printing, a type of direct contactless microfabrication technology, is a versatile fabrication process that enables a wide range of micro/nanopattern arrays by applying a strong electric field between the nozzle and the substrate. In general, the morphology and the thickness of polymers/quantum dot micropatterns show a systematic dependence on the diameter of the nozzle and the ink composition with a fully automated printing machine. The purpose of this report is to provide typical examples of e-jet printed micropatterns of polymers/quantum dots to explain the effect of each process variable on the result of experiments. Here, we demonstrate several operating conditions that allow high-resolution printing of layers of polymers/quantum dots with a precise control over thickness and submicron lateral resolution.

• Korean Journal of Construction Engineering and Management
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• v.5 no.1 s.17
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• pp.107-113
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• 2004

The advent of Radio Frequency Identification (RFID) technology has created new opportunities for improving the material management function in the construction industry and is starting to provide major improvements in the efficiency of the material management process. The objective of the research reported herein was to introduce the benefits of RFID technology on material management in the construction industry. RFID technology is discussed and various aspects of this technology are investigated. Potential RFID applications on material management proposed by Construction Industry Institute (CII) Breakthrough Strategy Committee (BTSC) and Fully Integrated and Automated Technology (FIATECH) are spelled out Finally, business analysis of RFID to estimate its impact is provided. It is concluded that there is a significant potential for improvement of material management function in the construction industry through the use of RFID.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.6
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• pp.34-41
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• 1993

This paper describes an effort to develop a microcomputer-based parameter identification system for three phase and two phase brushless DC motor. Back EMF equation is derived from back EMF waveform of three phase and two phase brushless DC motor. In this paper, a new identification algorithm for the brushless DC motor parameters by Pasek's technique is de veloped. It is found that Pasek's equation is valid for the brushless DC motor, too. The results obtained clearly shows that it is possible to implement the identification system for the determination of the brushless DC motor parameters. To minimize errors due to the ripple component in the measured armature current, dlgital averaging filter is employed. The whole identification process of signal generation, measuring, parameter determination is fully automated. The use of the pmpased method in the parameter identification system shows that the averaged current curve is in excellent agreement with the estimated current curve. Therefore, this close agreement conf i i the validity of this technique.