• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.269-272
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• 2004

The target of this paper is the development of Web-based monitoring & control system which is for effective and economic management of mold manufacturing process. This system has three module; G-code Control, Monitoring Module and Result analysis module. Also, as the environment of development is based on internet, this system which is possible to the remote site management of manufacturing process works on Web. To be possible to control the manufacturing monitoring by client, each module is made ActiveX control and is based on socket communication. This system makes the foundation which is possible to manage the mold manufacturing process efficiently from remote site by matching real-time monitoring with manufacturing process in factory using G-code control and displaying the result of manufacturing using Ch-CGI.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.373-380
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• 1998

The contribution of this paper is to provide the methods for the production automation of potato microtuber using the vision process in growth monitoring. The first method deals with computation for the growth density in the primary growth process. The second method addresses cognition process to identify the number and the volume of potato microtuber in secondary growth process. The third is to decide whether potato microtubers are infected by a virus or bacteria in growth process. The computation for the growth density in the primary growth process uses the method of Labeling. The second and third methods use template matching based on color patterns. With the developed method using vision process, this experiment is capable of discriminating weekly growth-rate in primary growth process, 85% cognition rate in secondary process and identifying whether there are infections. Therefore, we conclude that our experimental results are capable of growth monitoring for mass production of potato microtubers.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.3
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• pp.34-40
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• 2003

This paper describes evaluation and monitoring methods of machining characteristics for developed micro grooving machine. Experiments were conducted under various process conditions such as spindle revolution speed, feed rates and depth of groove V and U shape of blade and STD11 were used in this experiment. The status of grooving was evaluated through analysis of the Acoustic emission (AE) signal resulted in each process condition. Based on the analysis, this paper examined the possibility of monitoring adapting fuzzy logic. In conclusion, this paper presented the possibility of monitoring in process adapting AE technology and appropriate micro grooving condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.200-205
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• 1996

Recently, in order to achieve high flexibility of manufacture, monitoring and control strategies cf a new type have been developed. Since the generation of built-up edge on the cutting tool damages the surface finish of the workpiece, the monitoring system of built-up edge is an important process monitoring. In this study, the analyzing methods of cutting force signal to detect the built-up edge during cutting process are described. The cutting force signals are analyzed using the mean, standard deviation and mean to standard deviation of this cutting signals. We can obtain the guide to detect the built-up edge during turning process.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.67-72
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• 1997

Recently, in order to achieve high flexibility of manufacture, monitoring and control strategies of a new type have been developed. Since the generation of built-up edge on the cutting tool damages the surface finish of the workpiece, the monitoring system of built-up edge is an important process monitoring. In this study, the analyzing methods of cutting force signal to detect the built-up edge during cutting process are described. The cutting force signals are analyzed using the mean, standard deviation and mean to standard deviation of this cutting signals. We can obtain the guide to detect the built-up edge during turning process.

• Transactions of Materials Processing
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• v.18 no.2
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.09a
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• pp.121-125
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• 2005

In this paper, the web-based monitoring system is developed for the process monitoring of mold manufacturing. The cutting force is measured by hall-sensors which is low cost and useful to be installed in machine tool indirectly. Specially, the current of main spindle in machine tool is converted into cutting force by various experiments. For effective emote monitoring, the interface that is able to offer the information of current process and cutting signal to client is establish.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.11-21
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• 1992

Modern manufacturing process requires machine intelligence to meet the demands for high technology products as well as intelligence-based operating skills to lessen human worker's intervene. To meet this trend there has been wide spread interest in applying artificial neural network(ANN) to the areas of manufacturing process monitoring and control. This paper addresses application problems in such processes as welding, assembly, hydroforming process and inspection of solder joints.

• Journal of Power System Engineering
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• v.4 no.2
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• pp.25-30
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• 2000

The grinding process is very complex and relates many parameters to control the process. As this reason, a theoretical analysis and a quantitative estimation of the grinding process has not been well established. In this study, the in-process monitoring system was suggested by applying the neural network for monitoring and shooting the malfunction of cylindrical plunge grinding process. This system used the power signals from the electric power meter. This neural network was composed of processing elements [4-(5-5)-3] with 4 identified power parameters. Because sensitivity is blunted some minute vibration components, the simulation result of this system has appeared about 10% erroneous recognition in the uncertain pattern and the average success rate of the trouble recognition was about 90%. Consequently, the developed system, which applied to the power signals, can be recognize enough to monitor the grinding process as in-process.