• 제목/요약/키워드: u-Machine

검색결과 401건 처리시간 0.035초

u-Manufacturing을 위한 M2M 표준화 및 진보된 Machine Concept (M2M Standard Model and Advanced Machine Concept for u-Manufacturing)

  • 김동훈;송준엽;차석근
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2006년도 춘계학술대회 논문집
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    • pp.345-346
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    • 2006
  • In the future, a machine will be more improved in the form of advanced concept with collaborative ability in M2M(Machine to Machine, Mobile to Machine) environment for u-Manufacturing system. This paper tried to standardize M2M and design advanced concept machine. The M2M is front-end system for implementing autonomous ubiquitous environment. The advanced machine in M2M will be a collaborative machine with knowledge-evolutionary ability such as u-Machine(Ubiquitous machine), Vortal(Vertical Portal) machine and P2P(Peer to Peer) machine. Such advanced concept machines will be the key subject for M2M cooperation.

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U - Machine

  • 김선호
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2004년도 춘계학술대회 논문요약집
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    • pp.201-201
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    • 2004
  • 200여 년 전 탄생한 기계는 전기 에너지를 동력으로 사용하게 되면서 근 발전의 전기를 이루었다. 2차 세계대전이 종료된 후 발명된 NC는 정밀가공 기술의 발전을 가져왔으며 마이프로세서 기술을 채용한 CNC는 가공기술 측면에서는 초정밀 초고속을 가능하게 하고, 운영기술 측면에서는 지능화 연구를 가능하게 하고, 관리기술 측면에서는 FMS, CIM과 같은 유연성 있는 가공 시스템의 구축을 가능하게 했다.(중략)

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설비능력과 작업순서를 고려한 U-라인상에서의 셀 시스템 설계 (Operation-sequence-based Approach for Designing a U-shaped Independent-Cell System with Machine Requirement Incorporated)

  • 박연기;성창섭;정병호
    • 한국경영과학회지
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    • 제26권1호
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    • pp.71-85
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    • 2001
  • This paper considers a cost model for a U-shaped manufacturing cell formation which incorporates a required number of machines and various material flows together under multi-part multi-cell environment. The model is required to satisfy both the specified operation sequence of each part and the total part demand volume, which are considered to derive material handling cost in U-shaped flow line cells. In the model several cost-incurring factors including set-up for batch change-over, processing time for operations of each part, and machine failures are also considered in association with processing load and capacity of each cell. Moreover, a heuristic for a good machine layout in each cell is newly proposed based on the material handling cost of each alternative sequence layout. These all are put together to present an efficient heuristic for the U-shaped independent-cell formation problem, numerical problems are solved to illustrate the algorithm.

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Hair Pin Bending Machine을 이용한 동 튜브 굽힘 성형가공에 관한 연구 (A study about shape processing for the bend of the Copper-Tube that use Hair Pin Bending Machine)

  • 강흥식;김동성;허신;홍성인
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2003년도 춘계학술대회 논문집
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    • pp.1705-1708
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    • 2003
  • The purpose of this study is to investigate the manufacturing technique on the U type Draw-Bending of inner grooved tube. This bending process make the U shape tube by Hair Pin Bending machine. The U type tube requires the quality of product that satisfy sufficient conditions for a heat exchanger. The mandrel components act the important roles that prevent wrinkles and keep the shape of cross section of bended tube at bending process. We performed the FEM simulation using LS-DYNA software and the bending test of inner groove tube and then, compared bending simulation with bending test results about mandrel ball diameter, mandrel position and optimal clearance between mandrel and tube.

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Analyzing Factors Contributing to Research Performance using Backpropagation Neural Network and Support Vector Machine

  • Ermatita, Ermatita;Sanmorino, Ahmad;Samsuryadi, Samsuryadi;Rini, Dian Palupi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권1호
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    • pp.153-172
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    • 2022
  • In this study, the authors intend to analyze factors contributing to research performance using Backpropagation Neural Network and Support Vector Machine. The analyzing factors contributing to lecturer research performance start from defining the features. The next stage is to collect datasets based on defining features. Then transform the raw dataset into data ready to be processed. After the data is transformed, the next stage is the selection of features. Before the selection of features, the target feature is determined, namely research performance. The selection of features consists of Chi-Square selection (U), and Pearson correlation coefficient (CM). The selection of features produces eight factors contributing to lecturer research performance are Scientific Papers (U: 154.38, CM: 0.79), Number of Citation (U: 95.86, CM: 0.70), Conference (U: 68.67, CM: 0.57), Grade (U: 10.13, CM: 0.29), Grant (U: 35.40, CM: 0.36), IPR (U: 19.81, CM: 0.27), Qualification (U: 2.57, CM: 0.26), and Grant Awardee (U: 2.66, CM: 0.26). To analyze the factors, two data mining classifiers were involved, Backpropagation Neural Networks (BPNN) and Support Vector Machine (SVM). Evaluation of the data mining classifier with an accuracy score for BPNN of 95 percent, and SVM of 92 percent. The essence of this analysis is not to find the highest accuracy score, but rather whether the factors can pass the test phase with the expected results. The findings of this study reveal the factors that have a significant impact on research performance and vice versa.

Ubiquitous-Based Mobile Control and Monitoring of CNC Machines for Development of u-Machine

  • Kim Dong-Hoon;Song Jun-Yeob
    • Journal of Mechanical Science and Technology
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    • 제20권4호
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    • pp.455-466
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    • 2006
  • This study was an attempt to control and monitor Computerized Numerical Controller (CNC) machines anywhere and anytime for the development of a ubiquitous machine (u-machine). With a Personal Digital Assistant (PDA) phone, the machine status and machining data of CNC machines can be monitored in wired and wireless environments, including the environments of IMT2000 and Wireless LAN. Moreover, CNC machines can be controlled anywhere and anytime. The concept of the anywhere-anytime controlling and monitoring of a manufacturing system was implemented in this study for the purpose of u-manufacturing and u-machines. In this concept, the communication between the CNC controller and the PDA phone was successfully performed anywhere and anytime for the real-time monitoring and control of CNC machines. In addition, the interface between the CNC controller and the developed application module was implemented by Object linking and embedding for Process Control (OPC) and shared CNC memory. For communication, the design of a server contents module within the target CNC was based on a TCP/IP. Furthermore, the client contents module within the PDA phone was designed with the aid of embedded c++ programming for mobile communication. For the interface, the monitoring data, such as the machine status, the machine running state, the name of the Numerical Control (NC) program, the alarm and the position of the stage axes, were acquired in real time from real machines with the aid of the OPC method and by sharing the CNC memory. The control data, such as the start, hold, emergency stop, reserved start and reserved stop, were also applied to the CNC domain of the real machine. CNC machines can therefore be controlled and monitored in real time, anywhere and anytime. Moreover, prompt notification from CNC machines to mobile phones, including cellular phones and PDA phones, can be automatically realized in emergencies.

전립선암의 정확한 진단을 위한 질감 특성 분석 및 등급 분류 (Analysis of Texture Features and Classifications for the Accurate Diagnosis of Prostate Cancer)

  • 김초희;소재홍;박현균;;;;최흥국
    • 한국멀티미디어학회논문지
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    • 제22권8호
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    • pp.832-843
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    • 2019
  • Prostate cancer is a high-risk with a high incidence and is a disease that occurs only in men. Accurate diagnosis of cancer is necessary as the incidence of cancer patients is increasing. Prostate cancer is also a disease that is difficult to predict progress, so it is necessary to predict in advance through prognosis. Therefore, in this paper, grade classification is attempted based on texture feature extraction. There are two main methods of classification: Uses One-way Analysis of Variance (ANOVA) to determine whether texture features are significant values, compares them with all texture features and then uses only one classification i.e. Benign versus. The second method consisted of more detailed classifications without using ANOVA for better analysis between different grades. Results of both these methods are compared and analyzed through the machine learning models such as Support Vector Machine and K-Nearest Neighbor. The accuracy of Benign versus Grade 4&5 using the second method with the best results was 90.0 percentage.

IT 융합보안에서의 위협요소 분석 (Analysis of Threats Factor in IT Convergence Security)

  • 이근호
    • 한국융합학회논문지
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    • 제1권1호
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    • pp.49-55
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    • 2010
  • 정보통신기술 발전에 따라 많은 장치들간의 통신과 네트워킹의 수용이 이뤄지고 있다. 장치간의 통신을 위한 융합 사업이 빠르게 발전되어지고 있다. IT 융합 통신은 무선통신에서 차후 개척분야의 하나로 여겨지고 있다. 본 논문에서는 IT 융합 구조에서 M2M, 지능형 자동차, 스마트그리드, U-헬스케어에 대한 보안 위협요소를 분석하였다. 임베디드 시스템 보안, 포렌식 보안, 사용자 인증과 키관리 기법에 대한 IT 융합 보안의 방향을 제안하였다.

u-Manufacturing needs M2M (Machine to Machine) for Ubiquitous Computing World

  • Cha, Suk-Keun;Song, Jun-Yeob;Choi, Jin-Seok
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1112-1114
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    • 2005
  • Core position of the M2M (Machine to Machine) is device integration fusion using an emerging wireless and next internet technologies as well as IEEE 802.x, Bluetooth, Zigbee, DMB, Wibro etc. for ubiquitous environment that is complementary with IT839 strategy from Ministry of Information & Communication. This paper define and deploy about major functional requirements of M2M devices and middleware for how to it works, worldwide M2M technology trend & activities with its current & future application in manufacturing area that is called u-Manufacturing (Ubiquitous Manufacturing).

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