• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.799-804
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• 1990

In the blade grinding process, Blade image is captured. It is captured in the environment with vibration, using monochrome CCD camera with high speed electronic shutter. The image is preprocessed using LoG filter and zero crossing. We used Hough transformation to detect straight lines from the preprocessed image. From the equations of detected lines, we calculated width between lines caused by grinders. This paper proposes automatic measurement of blade width to automate the process control of blade grinding line.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.269-272
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• 2003

Industry is now seeing a dramatic increase in robot simulation and off-line programming. In order to use off-line programming effectively, the simulated workcell has to be identical to the real workcell. This requires an efficient and accurate method for the workcell calibration. Currently used techniques in the industry, however, are typically time-consuming, expensive and therefore not suitable for in-process application. This is because most of these techniques are based on the so-called “absolute calibration” method. In contrast to absolute method, relative calibration only measures the difference of an interested object relative to a standard reference. Owing to the small measurement range requirement, relative calibration method is very cheap and can achieve very high accuracy. In this paper the relative method is applied to calibrate an entire grinding workcell. Linear gauge is the only measurement device used. This workcell calibration includes tool center point (TCP) calibration and work object frame calibration. Due to the efficiency of the calibration algorithm and the simplicity of the calibration setup, the described calibration procedure can be done in process.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.736-740
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• 1991

EEG(Electroencephalogram) background signals can be represented as the sun of a conventional AR(Autoregressive) process and an innovation process, or a prediction error process. We have seen that conventional estimation techniques. such as least square estimates(LSE) or Gaussian maximum likelihood estimates(MLE-G) are optimal when the innovation process satisfies the Gaussian or presumed distribution. But when the data are contaminated by outliers, or artifacts, these assumptions are not met and conventional estimation techniques can badly fall and be strongly biased. It is known that EEG can be easily affected by artifacts. So we suggest a robust estimation technique which considerably performs well against those artifacts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.369-373
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• 2001

In this paper, we proposes the steps adopted to construct the neural network model for GMAW welds. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters are influenced by numerous factors, such as welding current, arc voltage, torch travel speed, electrode condition and shielding gas type and flow rate etc. In traditional work, the structural mathematical models have been used to represent this relationship. Contrary to the traditional model method, neural network models are based on non-parametric modeling techniques. For the welding process modeling, the non-linearity at well as the coupled input characteristics makes it apparent that the neural network is probably the most suitable candidate for this task. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.261-269
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• 2015

Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1460-1464
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• 2003

This paper describes the design and implementation techniques of a generic Internet based telerobotic system. The purpose is to make precious technical information and hands-on experience of the authors widely available for the research community. The paper is based on the telerobotics system that the authors recently implemented between KAIST and Saga University, Japan. In its current functionality, two control modes can be exercised; high-level supervisory control, and low-level supervisory control.

• Journal of Korean Society for Quality Management
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• v.34 no.4
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• pp.33-39
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• 2006

These days manufacture technology and manufacture environment are changing rapidly. By development of computer and enlargement of technique, most of manufacture field are computerized. In order to win international competition, it is important for companies how fast get the useful information from vast data. Statistical process control(SPC) techniques have been used as a problem solution tool at manufacturing process until present. However, these statistical methods are not applied more extensively because it has much restrictions in realistic problems. These statistical techniques have lots of problems when much data and factors are analyzed. In this paper, we proposed more practical and efficient a new statistical design technique which integrated data mining (DM) and statistical methods as alternative of problems. First step is selecting significant factor using DM feature selection algorithm from data of manufacturing process including many factors. Second step is finding optimum of process after estimating response function through response surface methodology(RSM) that is a statistical techniques

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.680-687
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• 1995

In recent years, grinding techniques for precision machining of brittle materials used in electric, optical and magnetic parts have been improved by using superabrasive wheel and precision grinding machine. The completion of optimum dressing of superabrasive wheel makes possible the effective precision grinding of brittle materials. But the present dressing system cannot have control of optimum dressing of the superabrasive wheel. This study has proposed a new optimum in-process electrolytic dressing system. This system can carry out optimum in-process dressing of superabrasive wheel, and give very effective control according to gap increase.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.113-120
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• 1994

The dynamic characteristics of turning processes are complex, non-linear and time-varying. Consequently, the conventional techniques based on crisp mathematical model may not guarantee cutting force regulation. This paper presents a fuzzy controller which can regulate cutting force in turning process under varying cutting conditions. The fuzzy control rules are extablished from operator experience and expert knowledge about the process dynamics. Regulation which increases productivity and tool life is achieved by adjusting feedrate according to the variation of cutting conditions. The performance of the proposed controller is evaluated by cutting experiments in the converted conventional lathe. The results of experiments show that the proposed fuzzy controller has a good cutting force regulation capability in spite of the variation of cutting conditions.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1191-1200
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• 2008

Recently classroom monitoring is becoming important since the lecture is being held in the classroom and academic institutions are interested in the quality assurance. Some institutions have adopted ISO 9000 systems and constructed monitoring system through measurement, analysis and improvement. In this study quality assurance problems in academic institutions and the requirements of ISO 9001:2000 will be briefly discussed. Next we will investigate how to monitor the lecture in the classroom(in-class) using statistical process control techniques such as control charts. Then case study will be given to illustrate the technique to use appropriate statistics. Finally how to monitor the learning process during in-class and after-class will be proposed.