• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.411-416
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• 1993

In order to achieve computer-oriented control and automation of manufacturing processec, a distributed NC (DNC_) system was developed for FMS under the Windows environment. The DNC system consists of conventional DNC, PMC interface and tool management modules. Real-time system conditon monitoring and control fuctions required for machine tools and machining processes were accomplished by developing a PMC interface module called MMC board. Tool condition monitoring and management was performed by the developed tool management module composed of a tool setting probe and softwares. Performance of the DNC system was confirmed on the horizontal and the vertical type machining center equipped with FANUC OMC for the large amount of experiments.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 춘계학술대회
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• pp.241-248
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• 2000

Increased complexity of products and their manufacturing processing demans higher quality control and monitoring than ever before. Therefore, flexible automatization or flexible manufacturing systems (FMS) offer numerous advantages over alternative manufacturing methods. In this state, a in-process monitoring is one of the important flexible automation system. And as use of NC and CNC machine tool has been increasing, cutting work has automating and it is necessary to develop the automatic production system combined a couple of machine tool. Thus, in this paper to search examination it can measure the tool wear and the tool life and can be more practical research subject.

• 한국정밀공학회지
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• 제13권9호
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• pp.31-37
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• 1996

This Paper is concerned with effective signal identification method for tool breakage and micro chipping using discrete wavelet transform of feed motor current in milling operations. The wavelet transform uses an analyzing waveletfunction which is localized in both frequency and time domain to detect subtle time localized changes in input signals. The changing pattern of wavelet coefficient is continuously compared to detect tool breakage and micro chipping over one spindle revolution. The results indicate that the wavelet transform can identify tool failure with much greater sensi- tivity than the time domain monitoring and frequency domain monitoring such as FFT. Experimental results are presented to support the proposed scheme.

• 한국생산제조학회지
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• 제4권2호
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• pp.38-45
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• 1995

The diagnosis and monitoring system of abnormal cutting condition is necessary to realize precision machining proces and factory automation, which are final goal of metal cutting in order to develop this system, theimage processing technique has been investigated in machining process. In theis paper, the measurement system of tool wear using computer vision is designed to detect the wear pattern by non-contact and direct method and get the realiable wear information about cutting tool. We measured the area of the side and front part of the diamond core dril which is used in 40kHz ultrasonic vibration machine.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(2)
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• pp.93-96
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• 2002

It is said that the verification effort occupies about 50-70 percent of the total effort of a System-On-A-Chip. This paper aims to develop a test bench automation tool based on the abstraction of the interface protocols. This tool will allow designers to describe their test benches in a high level language such as C rather than VHDL or Verilog. It helps designers to save their verification time and effort.

• 한국정밀공학회지
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• 제28권3호
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• pp.363-369
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• 2011

In this study, a direct pattern forming process on a plastic film using ultrasonic vibration energy is investigated. A tool horn containing micro-patterns is attached to an ultrasonic power supply, and is used to press a plastic film with ultrasonic vibration in order to replicate micro-patterns on the surface of the plastic film. To replicate micro-patterns with high accuracy, the tool horn should be designed to allow only the longitudinal vibration, not the transverse vibration. For this purpose, the design of a tool horn is investigated through finite element analysis, from which the resulting natural frequency of the tool horn can be adjusted in the range of the ultrasonic power supply. The analysis result is then reflected on the optimal design and fabrication of the tool horn. The validity of the developed tool horn is discussed through pattern-forming experiments using the ultrasonic vibration of the developed tool horn.

• 전기학회논문지
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• 제60권5호
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• pp.913-920
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• 2011

Distribution systems for operating the various systems should be operated organically. Distribution systems for organic operations extend the functionality of the system and system integration for the extension is doing. However, in systems integration for each unique non-standard definition of linkage and exchange systems are used. Non-standard definition of a unique linkage and exchange systems in the maintenance and expansion will result in many negative results. To solve these problems, the system and the exchange of information about the links between systems should define standards. IEC (International Electrotechnical Commission) power to solve these problems in the field of the Common Information Model (Common Information Model, CIM) standard (IEC61970, IEC61968) is defined as the transmission and distribution system integration and standardization for the exchange of information. In this paper, standardized system for building CIM-based distribution automation system should describe the process of building. In addition, the process of establishing a common information model needed (CIM) defined and associated services for a defined set of models is proposed in the standardization process.

• International Journal of Contents
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• 제13권1호
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• pp.38-44
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• 2017

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

• 한국철도학회논문집
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• 제8권5호
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• pp.425-433
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• 2005

For the design of welded bogie frame, the concept of multidisciplinary engineering activities, i.e. static, fatigue and dynamic analysis, has been applied, in which the sharing of design parameters related with each analysis and the collaboration of the working parts in charge should be fulfilled. However, in spite of these necessities, the multi-disciplinary engineering activities couldn't be performed in practice due to tack of the automation of the required analysis. In this paper, an automation of fatigue durability analysis of welded bogie frame according to UIC-Code was proposed by using the Model Center, which enables to integrate the several tools for the fatigue durability analysis, i.e. I-DEAS, ANSYS and BFAP, and to perform iterative analysis works in relation to the geometrical change of transom support bracket. Besides, the wrapping programs to control I/O-data and interfaces of these tools were developed. The developed automation technique brings not only significant decreasing man-hour required in the durability analysis, but also providing a platform of the multidisciplinary engineering activities.

• 산업경영시스템학회지
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• 제43권4호
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• pp.208-216
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• 2020

With the spread of smart manufacturing, one of the key topics of the 4th industrial revolution, manufacturing systems are moving beyond automation to smartization using artificial intelligence. In particular, in the existing automatic machining, a number of machining defects and non-processing occur due to tool damage or severe wear, resulting in a decrease in productivity and an increase in quality defect rates. Therefore, it is important to measure and predict tool life. In this paper, ν-ASVR (ν-Asymmetric Support Vector Regression), which considers the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, was proposed and applied to the tool wear prediction problem. In the case of tool wear, if the predicted value of the tool wear amount is smaller than the actual value (under-estimation), product failure may occur due to tool damage or wear. Therefore, it can be said that ν-ASVR is suitable because it is necessary to overestimate. It is shown that even when adjusting the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, the ratio of the number of data belonging to ⲉ-tube can be adjusted with ν. Experiments are performed to compare the accuracy of various kernel functions such as linear, polynomial. RBF (radialbasis function), sigmoid, The best result isthe use of the RBF kernel in all cases