• Journal of the Korean Society of Industry Convergence
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• v.14 no.2
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• pp.45-52
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• 2011

Since the most exclusive machines of the modern industries which require the nano precision rates are evolved from the machine tools, the design of the stable machine tool structure is very critical. Exclusive machines for the modern industries such as semiconductor, solar cell and LED have surface machining processes which are similar to the face cutting and grinding of conventional machine tools. This study was initiated to stabilize a milling machine structure and further to help design those exclusive machines which have similar machining mechanisms. The vibrations inherent to the machine tool structures hurt the precision machining as well as damage the longevity of the structures. There have been numerous researches in order to suppress the vibrations of machine tool structures using the extra modules such as actuators and dampers. In this paper, the dynamic properties are analyzed to obtain the natural frequencies and mode shapes of a machine tool structure which reflect the main reasons of the biggest vibrations under the given operating conditions. And the feasibility of improving the stability of the structure without using any additional apparatus has been investigated with minor design changes. The result of the study shows that simple changes based on proper system identification can considerably improve the stability of the machine tool structure.

• Journal of Mechanical Science and Technology
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• v.20 no.1
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• pp.51-58
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• 2006

To compensate for the motion errors in hydrostatic tables, a method to actively control the clearance of a bearing corresponding to the amount of error using actively controlled capillaries is introduced in this paper. The design method for an actively controlled capillary that considers the output rate of a piezo actuator and the amount of error that must be corrected is described. The basic characteristics of such a system were tested, such as the maximum controllable range of the error, micro-step response, and available dynamic bandwidth when the capillary was installed in a hydrostatic table. The tests demonstrated that the maximum controllable range was $2.4\;{\mu}m$, the resolution was 27 nm, and the frequency bandwidth was 5.5 Hz. Simultaneous compensation of the linear and angular motion errors using two actively controlled capillaries was also performed for a hydrostatic table driven by a ballscrew and a DC servomotor. An iterative compensation method was applied to improve the compensation characteristics. Experimental results showed that the linear and angular motion errors were improved to $0.12{\mu}m$ and 0.20 arcsec, which were about $1/15^{th}$ and $1/6^{th}$ of the initial motion errors, respectively. These results confirmed that the proposed compensation method improves the motion accuracy of hydrostatic tables very effectively.

• IE interfaces
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• v.18 no.1
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• pp.73-81
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• 2005

Injection molding has been widely used in producing plastic parts in large quantities. However, its productivity mainly depends on the expertise and experience of skilled workers because of the difficulty and complexity to determine a robust injection molding condition which is not influenced by the minor operational variation of an injection molding machine and produces good parts continuously. This study analyzes the defect types of the parts and proposes a support system to assist users in determining the robust process condition. The support system calculates the start condition from the information of an injection mold, the injection molding machine, the resin used, and the part. Through the iterative step which updates the condition using the defect information of the part tested, users can obtain the initial condition which produces the part without any problem for the first time. The support system also assists users in obtaining the robust condition from the initial condition using the technique of experimental design. To prove the validity of the support system, this study implements it in the control panel of the injection molding machine.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.18-23
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• 2006

The formation degree of sustain (ITO pattern) determines the quality of a PDP (Plasma Display Panel). Thus, in the present study, we attempt to detect 100% of the defects that are larger than $30{\mu}m$. Currently, the inspection method in the PDP manufacturing process is dependent upon the naked eye or a microscope in off-line mode. In this study, a prototype inspection system for PDP ITO patterned glass is developed. The developed system, which is based on a line-scan mechanism, obtains information on the defects and sorts the defects by type automatically. The developed inspection system adopts a multi-vision method using slit-beam formation for minimum inspection time and the detection algorithm is embodied in the detection ability. Characteristic defects such as pin holes, substances, and protrusions are extracted using the blob analysis method. Defects such as open, short, spots and others are distinguished by the line type inspection algorithm. It was experimentally verified that the developed inspection system can detect defects with reliability of up to 95% in about 60 seconds for the 42-inch PDP panel.

• Journal of KIBIM
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• v.1 no.1
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• pp.1-5
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• 2011

Earthwork is important in terms of construction time and duration, and highly related to the construction productivity. However, current earthwork system has stick to labor intensive process depending on skilled operator's heuristic decision making, so it is hard to improve overall productivity. To overcome this drawback, this paper presents a BIM based Intelligent Excavation System(IES). The BIM technology is applied in the excavation task planning system, Human-Machine Interface for remote-control/autonomous work environment, and web-based Project Management Information System(PMIS) in the IES integration process, and the results are addressed.

• ETRI Journal
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• v.44 no.5
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.359-364
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• 2004

A high-speed and intelligent CNC system has been developed by Turbotek Co., Ltd. This paper presents the study for commercialization of the developed CNC system. In order to acquire stability and reliability of the developed CNC system, its hardwares and softwares ate improved. The CNC main unit is revised to a compact box-type CNC controller. Moreover, the integrated CNC main unit that has built-in and expandable I/O modules is also developed. Remote monitoring, fault diagnosis End NURBS interpolation functions are realized on the CNC system as software modules. Through these efforts, the developed CNC system can be loaded on machine tools successfully.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.572-575
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• 2004

Since the 1990s, the advancement of semiconductor technology has resulted in the development of microprocessor technology, auxiliary computer technology, and application technology such as intelligent algorithms (neural network, fuzzy, etc.). These based the development of intelligent machines. An agent is autonomous software that recognizes environment, exchanges knowledge with other agents and makes decisions. We designed agent-based sensor structure. For the purpose, first, it modeled the function of an intelligent machine. Second, it designed sensory function on the agent level.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.