• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.781-788
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• 2003

It is an essential process to predict behaviors of ground and structure to seek economical efficiency and stability on the given environment. Predictions are conducted through analysis process of ground and structure. For these analyses, exact and quick acquisition of measuring data is required. But we face many difficulties in data acquisition stages due to the conditions of construction site. Therefore development of a powerful and effective monitoring system that can manage the integration of database and the implementation of measuring process in real time is strongly desired. This article shows an actual example of application of internet based monitoring system compared with the conventional monitoring system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.313-317
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• 1996

This work deals with description of gas purifing system to product high pure helium gas using low temperature absorption. The system controls temperature of heaters, open/close of solenoid valves and levels of liquid nitrogen to purify a raw gas and continuously products purified gas with perfoming alternatively purification and regeneration. We develop the monitoring and control program to monitor the gas purification process on real-time and control the process time with checking the impurities in purified gas. From the result of system operation, the developed monitoring and control system continuously products high pure helium gas with reducing impurities in raw gas to permitted limits(less than 0.01 ~ 0.05 ppm)

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2390-2392
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• 1998

In this paper, we discuss the development of monitoring system with data process equipment which transfers data from Remote Terminal Unit(RTU) to monitoring computer. The RTUs sense temperature, pressure and PLC(Programmable Logic Controller) nodes conditions of scrubber in semiconductor manufacture processing. The data Process equipment is connected every RTU and a monitoring computer through serial communication. This equipment receives informations from RTU, process data, and transfers them to monitoring computer. To avoid congestion in data communication, task scheduling algorithm used RT O/S(Real-Time Operating System) is embedded in ROM which is a part of data Process equipment.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.1
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• pp.1-5
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• 2011

To enter next process control, numerous approaches, including run-to-run (R2R) process control and fault detection and classification (FDC) have been suggested in semiconductor manufacturing industry as a facilitation of advanced process control. This paper introduces a novel type of optical plasma process monitoring system, called plasma eyes chromatic system (PECSTM) and presents its potential for the purpose of fault detection. Qualitatively comparison of optically acquired signal levels vs. process parameter modifications are successfully demonstrated, and we expect that PECSTM signal can be a useful indication of onset of process change in real-time for advanced process control (APC).

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.387-390
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• 1997

Grinding process takes a long time that grinding machine is setted properly. It is difficult for user to judge correctly the abnormal states generated in grinding process. Air grinding has to be reduced for the improvement of productivity. In addition, it is important to monitor the dressing and the grinding process so that the grinding working maintains optimal grinding conditions. In this study, the monitoring system using the acoustic emission is developed to monitor these processes continuously. This system was able to reduce the preparation as well as the machine setting time in grinding operation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1386-1390
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• 2007

This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.

• Journal of the Korea Safety Management & Science
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• v.2 no.4
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• pp.19-32
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• 2000

Assignable causes producing temporary deviation from the underlying system can influence on process adjustment and process monitoring in dynamic feedback control system. In this paper, the impact of assignable causes on EWMA forecasts and process adjustment which is based on the EWMA forecasts are derived for optimum control methods.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.14-21
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• 1998

The in-process detection of the state of cutting tool is one of the most important technical problem in Intelligent Machining System. This paper presents a method of detecting the state of cutting tool in turning process, by using Artificial Neural Network. In order to sense the state of cutting tool. the sensor fusion of an acoustic emission sensor and a force sensor is applied in this paper. It is shown that AErms and three directional dynamic mean cutting forces are sensitive to the tool wear. Therefore the six pattern features that is, the four sensory signal features and two cutting conditions are selected for the monitoring system with Artificial Neural Network. The proposed monitoring system shows a good recogniton rate for the different cutting conditions.

• Journal of Welding and Joining
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• v.28 no.4
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• pp.81-86
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• 2010

In resistance spot welding, regardless of the optimal condition, bad weld quality was still produced due to complicated manufacturing processes such as electrode wear, misalignment between the electrode and workpiece, poor part fit-up, and etc.. Therefore, the goal of this study was to measure the process signal which contains weld quality information, and to develop the process fault monitoring system. Welding force signal obtained through variety experimental conditions was analyzed and divided into three categories: good, shunt, and poor fit-up group. And then a monitoring algorithm made up of an artificial neural network that could estimate the process fault of each different category based on pattern was developed.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.821-826
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• 2001

Out of all metal-cutting processes, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. Accordingly, this paper deals with Basic system and Online system. Basic system comprised of spindle rotational speed, feed rates, thrust, torque and flank wear measured tool microscope. Online system comprised of spindle rotational speed, feed rates, AE signal, flank wear area measured computer vision. On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.