• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.653-658
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• 2000

For testing machine tools, we used test the work by measure of 3-D object that it was made by the machine tool. By reason of these, we have spent to the cost of measure and have delayed supply to user. In this study, we made a macro-program and a application program in order to test automatic the machine tool. So, if you constitute a ring core and a touch prove in machine tool, you should test the property of machine tool.

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.75-83
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• 2011

Unified Modeling Language (UML) is widely accepted in industry and particularly UML State Machine Diagram is popular for describing the dynamic behavior of classes. This paper discusses deadlock detection of System using UML State Machine Diagram. Since a State Machine Diagram is used for indivisual class' behavior, all the State Machine Diagrams of the classes in the system are combined to make a big system-wide State Machine Diagram to describe system behavior. Generally this system-wide State Machine Diagram is very complex and contains invalid state and transitions. To make it a usable and valid State Machine Diagram, synchronization and externalization are applied. The reduced State Machine Diagram can be used for describing system behavior thus conventional model-checking technique can be applied. This paper shows how deadlock detection of system can be applied with simple examples. All the procedures can be automatically done in the tool.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.1-9
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• 2005

This paper proposes the heuristic algorithm for the generalized GT problems to consider the restrictions which are given the number of machine cell and maximum number of machines in machine cell as well as minimum number of machines in machine cell. This approach is split into two phase. In the first phase, we use the similarity coefficient which proposes and calculates the similarity values about each pair of all machines and sort these values descending order. If we have a machine pair which has the largest similarity coefficient and adheres strictly to the constraint about birds of a different feather (BODF) in a machine cell, then we assign the machine to the machine cell. In the second phase, we assign parts into machine cell with the smallest number of exceptional elements. The results give a machine-part grouping. The proposed algorithm is compared to the Modified p-median model for machine-part grouping.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.137-140
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• 2003

Recently, as the demand of small-sized precision parts is rising in precision industry such as mobile, automobile, optic. etc. the requirement of small-sized machine tool is increasing. Desktop machine tool define small-sized machine tool that is able to install in table. According to diminishing in size, Desktop machine tool is able to economize production cost by reducing work area and consuming electric power. But Desktop machine tool generates vibration in acceleration and deceleration modes by inertia force of moving part. Also vibration is generated when it move simultaneously two axis or three axis. Such generating vibration situation is reason of declining stiffness of machine tool structure because of smallizing in size. And this vibration has a large effect on precision of machining products. Therefore, evaluating of the control characteristic is necessary for minimizing vibration of machine tool as much as possible to accomplish precision machining of small-sized parts

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.360-367
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• 2002

The machine-part group formation is to group the sets of parts having similar processing requirements into part families, and the sets of machines needed to process a particular part family into machine cells. The purpose of this study is to develop a two-phase machine-part group formation algorithm based on Self-Organizing Maps (SOM). In phase I, it forms machine cells from the machine-part incidence matrix by means of SOM whose output layer is one-dimension and the number of output nodes is the twice as many as the number of input nodes in order to spread out the input vectors. In phase II, it generates part families which are assigned to machine cells by means of machine ratio related with processing part and it gives machine-part group formation. The proposed algorithm performs remarkably well in comparison with many well-known algorithms for the machine-part group formation problems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.954-957
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• 2005

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence is applied for many industrial product and machine tools are the center of manufacturing devices in intelligent manufacturing system. The purpose of this paper is to present the construction of Rule Base for knowledge structure that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It constructs Rule Base of knowledge used of machine toots. The constructed Rule Base facilitates the effective operation and control of machine tools and will provide a systematic way to integrate the expert's knowledge that will apply Intelligent Machine Tools.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.303-308
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• 2018

Demand is increasing rapidly in recent years than supply to machine learning professionals. To alleviate this gap, user-friendly machine learning software that can be used by non-specialists has emerged, which is Machine Learning-as-a-Service(MLaaS). MLaaS provides services that enable businesses to easily leverage ML capabilities without expertise. In this paper, we will compare and analyze features, interfaces, supporting programming language, ML framework, and Machine Learning services of MLaaS, to help companies easily use ML service.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.360-370
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• 2022

Demand for machine learning systems continues to grow, and cloud machine learning platforms are widely used to meet this demand. Recently, the performance improvement of the application processor of smartphones has become an opportunity for the machine learning platform to move from the cloud to On-Device AI, and mobile applications equipped with machine learning functions are required. In this paper, machine learning tools for mobile applications are investigated and compared the characteristics of these tools.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.958-962
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• 2003

We acquired data of injection molding machine in operation and stored the data in database. We acquired the data of injection molding machine for fault detection and diagnosis (FDD) continuously and estimated the fault results with a fuzzy algorithm. Many of FDD are applied to a huge system, nuclear power plant and a computer numerical control(CNC) machine for processing machinery. But, the research of FDD is rare in injection molding machine compare with computer numerical control machine. We appraise the accuracy of the FDD and the limit of the application to the injection molding machine. We construct the fault detection and diagnosis system based on fuzzy algorithm in the injection molding machine. Data of operating injection molding machine are acquired in order to improve the reliability of detection and diagnosis.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.4
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• pp.77-84
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• 2003

The properties of a machine tool greatly affect machining quality since a machine tool has large variance in its features. Machine tool makers want to find best machining condition with the one that they have built. Machine builders need to develop test specimen since it helps finding characteristics of machine tools when the machining properties of the specimen are analyzed. This paper develops test specimen to identify features of the main spindle, the feeding device, and the frame of a machine tool. The specimen is machined with a high speed machine and the features of the machine are analyzed with test items. They are surface roughness, overshoot in axial movement, errors in circular movement, feeding with small movement and compensational error. This work can improve usability for a machine tool in machining practice.