• Composites Research
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• v.28 no.4
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• pp.212-218
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• 2015

A large composite spar was manufactured using an automatic fiber placement (AFP) machine. To verify its structural performance, the weakest part of the structure, which is called 'corner radius', was tested under bending and examined by finite element analysis. Since the application of AFP machine to composite structure fabrication is still in early stage in Korea, this paper presents the summary of whole process for manufacturing composite spar using AFP machine from mandrel design and analysis to verification test. The deflection and stress by mandrel weight and AFP machine force, thermal deformation and natural frequency were all examined for mandrel design. The target structure was composite C-spar and cured in an autoclave. Test results were compared with nonlinear finite element analysis results to show that the structure has the strength close to the theoretical value. It was confirmed that the corner radius of the spar manufactured by AFP process showed deviation less than 20% compared with first ply failure strength. The results indicate that the AFP technology could be used for large scale composite structure production in the near future.

• Composites Research
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• v.35 no.5
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• pp.303-308
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• 2022

PIC (Piecewise Integrated Composite) is a new concept for designing a composite structure with mosaically assigning various types of stacking sequences in order to improve mechanical properties of laminated composites. Also, machine learning is a sub-category of artificial intelligence, that refers to the process by which computers develop the ability to continuously learn from and make predictions based on data, then make adjustments without further programming. In the present study, the tapered box beam type PIC robot arm for carrying and transferring wide and thin LCD display was designed based on the machine learning in order to increase structural stiffness. Essential training data were collected from the reference elements, which were intentionally designated elements among finite element models, during preliminary FE analysis. Additionally, triaxiality values for each finite element were obtained for judging the dominant external loading type, such as tensile, compressive or shear. Training and evaluating machine learning model were conducted using the training data and loading types of elements were predicted in case the level accuracy was fulfilled. Three types of stacking sequences, which were to be known as robust toward specific loading types, were mosaically assigned to the PIC robot arm. Henceforth, the bending type FE analysis was carried out and its result claimed that the PIC robot arm showed increased stiffness compared to conventional uni-stacking sequence type composite robot arm.

• Composites Research
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• v.36 no.1
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• pp.53-58
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• 2023

The PIC design method is assigning different stacking sequences for each shell element through the preliminary FE analysis. In previous study, machine learning was applied to the PIC design method in order to assign the region efficiently, and the training data is labeled by dividing each region into tension, compression, and shear through the preliminary FE analysis results value. However, since buckling is not considered, when buckling occurs, it can't be divided into appropriate loading type. In the present study, it was proposed PIC-NTL (PIC design using novel technique for analyzing load type) which is method for applying a novel technique for analyzing load type considering buckling to the conventional PIC design. The stress triaxiality for each ply were analyzed for buckling analysis, and the representative loading type was designated through the determined loading type within decision area divided into two regions of the same size in the thickness direction of the elements. The input value of the training data and label consisted in coordination of element and representative loading type of each decision area, respectively. A machine learning model was trained through the training data, and the hyperparameters that affect the performance of the machine learning model were tuned to optimal values through Bayesian algorithm. Among the tuned machine learning models, the SVM model showed the highest performance. Most effective stacking sequence were mapped into PIC tube based on trained SVM model. FE analysis results show the design method proposed in this study has superior external loading resistance and energy absorption compared to previous study.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.672-675
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• 2005

To imprint 70-nm wide line-patterns, we used a newly developed ultraviolet nanoimprint lithography (UV-NIL) process in which an elementwise patterned stamp (EPS), a large-area stamp, and pressurized air are used to imprint a wafer in a single step. For a single-step UV-NIL of a 4' wafer, we fabricated two identical $5'\times5'\times0.09'(W{\times}L{\times}H)$ quartz EPSs, except that one is with nanopatterns and the other without nanopatterns. Both of them consist of 16 small-area stamps, called elements, each of which is $10\;mm\;\times\;10\;mm$. UV-curable low-viscosity resin droplets were dispensed directly on each element of the EPSs. The volume and viscosity of each droplet are 3.7 nl and 7 cps. Droplets were dispensed in such a way that no air entrapment between elements and wafer occurs. When the droplets were fully pressed between ESP and wafer, some incompletely filled elements were observed because of the topology mismatch between EPS and wafer. To complete those incomplete fillings, pressurized air of 2 bar was applied to the bottom of the wafer for 2 min. Experimental results have shown that nanopatterns of the EPS were successfully transferred to the resin layer on the wafer.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.792-795
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• 2005

The guide-ways of precision machine tools are one of important element of machine tools. It has usually a pair of surfaces for constraint of one direction with bearing. In the case of precision machine tools, non-contact bearing such as hydrostatic bearing and aerostatic bearing is adopted usually. In this case, profiles of rails has effect on straightness and the clearance of bearing has effect on stiffness of guide way, which changes to higher if clearance changes to smaller. The clearance is varied along moving table according to relative distance of pair of rails. The relative distance of pair of rail can be divided by three properties. First and second properties are straightness of each pair of rail and bearing pad. And, third is parallelism about pair of rails and pairs of bearing pad. There are several methods for measuring straightness of each surface such as reversal method, sequential two point method, and way straightness. These straightness measuring methods are always acquiring deviation of profile from eliminating linear fitted inclined line and don't have the information of parallelism. Therefore, to get the small clearance for high stiffness, the straightness of rail and bearing pad and parallelism about pair of rails and pair of bearing pads are measured for correction such as regrinding, reassembling and lapping. In this research, new and easy method for measuring parallelism of pair of rails is suggested. Two displacement probe and sensor stage, which is carry on the displacement sensor, are needed. The simulation and experiment was accomplished about pair of horizontal guide way to confirm the measurement of parallelism. And, the third probe is added to measure the straightness of each rails by sequential two point method. From the estimation of combined these two methods, it is confirmed that the profiles of a pairs of rails can be measured.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1043-1056
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• 2017

A styled document is a document that contains diverse decorating functions such as different font, colors, tables and images generally authored in a word processor (e.g., MS-WORD, Open Office). Compared to a plain-text document, a styled document enables a human to easily recognize a logical structure such as section, subsection and contents of a document. However, it is difficult for a computer to recognize the structure if a writer does not explicitly specify a type of an element by using the styling functions of a word processor. It is one of the obstacles to enhance document version management systems because they currently manage the document with a file as a unit, not the document elements as a management unit. This paper proposes a machine learning based approach to analyzing the logical structure of a styled document composing of sections, subsections and contents. We first suggest a feature vector for characterizing document elements from a styled document, composing of eight features such as font size, indentation and period, each of which is a frequently discovered item in a styled document. Then, we trained machine learning classifiers such as Random Forest and Support Vector Machine using the suggested feature vector. The trained classifiers are used to automatically identify logical structure of a styled document. Our experiment obtained 92.78% of precision and 94.02% of recall for analyzing the logical structure of 50 styled documents.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.336-342
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• 2007

Industrial HMI(Human Machine Interface) system is the main element among the factory automation processes and have been used to monitor and control operation and status of machine in factory with PLC. This HMI often brings heavy loads to the system development and difficult decreasing the system because it tends to use a specific system per each manufacturer. Therefore, in this thesis, we have developed an embedded linux-based embedded industrial HMI software modules which can be used for touch panel embedded system to solve these problem. In this module, we have used the Qt/Embedded software component because it can be used by all systems which support C++ compiler without modifying the existing codes. We can design more flexible system and network configuration because we have used the wireless communication module. In this thesis, we implement linux-based HMI software modules which are capable of wireless communication as well as bringing the mobility to the overall system and finally decreasing the system development loads by using the general purpose OS with competitive price.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.161-168
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• 2021

As the demand for high speed and high precision increases in the field of machine tool, interest in stiffness and vibration of machine tool is increasing. However, it takes a lot of time to develop a detailed design of machine tool based on experience, and it is difficult to design appropriately. Recently, structural optimization using FEM are increasingly used in machine tool design. But, it is difficult to optimize in consideration of the vibration state of the structure since optimization through stress distribution of a structure is mainly used, In this paper, Static structural analysis, mode analysis, and harmonic analysis using FEM were conducted to optimize the head structure that has the most influence on machining in a 5-axis machine tool. It is proposed a topology optimization analysis method that considers both static stiffness and dynamic stiffness using objective function design.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.2
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• pp.81-88
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• 2016

Machine-to-Machine (M2M) communication provides each component (machine) with access to Internet, evolving into the IoT technology. IoT is a trend where numbers of devices provide the communication service, using the Internet protocol. As spreading the concept of IoT(Internet of Things), various objects become home information sources. According to the wide spread of various devices, it is difficult to access data on the devices with unified manners. Under this environment, security is a critical element to create various types of application and service. In this paper propose the inter-device authentication and Centralized Remote Security Provisioning framework in Open M2M environment. The results of previous studies in this task is carried out by protecting it with the latest information on M2M / IoT and designed to provide the ultimate goal of future M2M / IoT optimized platform that can be integrated M2M / IoT service security and security model presents the information.