• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.15-21
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• 1995

Automatic monitoring of cutting process is one of the most important technologies for increasing the stability and the reliability of unmanned manufacturing system. In this study, the methods which use laser displacement signals and banded energy method are proposed to monitor chatter vibration in the turning process. From this method, the monitoring system of the chatter vibration was developed and investigated its practical possibility. As a result, it is shown by experiments that the chatter vibration can be detected accurately, and it can be widely used in most turning processes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.224-226
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• 2021

Recently, in order to increase the efficiency of the product production process, the automation of facilities and devices in the factory is in progress, and a smart factory is being built using ICT and IoT technologies. In order to organically solve many problems occurring in the smart factory, a system for monitoring the wireless communication function between facilities and devices and the manufacturing process environment of the smart factory is required. In this paper, we propose a monitoring system using a Bluetooth module, a temperature/humidity sensor and a fine dust sensor to remotely monitor the process environment of a smart factory. The proposed monitoring system collect Arduino sensor values wirelessly through Bluetooth communication.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.148-154
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• 2001

Drilling is one of the most important operations in machining industry and usually the most efficient and economical method of cutting a hole in metal. From automobile parts to aircraft components, almost every manufactured product requires that holes are to be drilled for the purpose of assembly, creation of fluid passages, and so on. It is therefore desirable to monitor drill wear and hole quality changes during the hole drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. A drill-wear monitoring system provides information about drill status. With the information, optimum planning for tool change is possible. And drill-wear monitoring system in needed to evaluated drilled hole quality and the wear of drill. Accordingly, this paper deals with an on-line drill wear monitoring system of the detection of tool wear with the computer vision and the area of the drill flank wear is analyzed quantitatively by the system.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.264-269
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• 2005

Advances in sensors, actuators, and computers and developments In information systems offer unprecedented opportunities to implement highly ambitious automation, control and decision strategies. There are also new challenges and demands for control and automation in modern industrial practices. There is a growing need for an active participation from the information systems in industrial, manufacturing and process industry environments because currently there are many control problems. This paper provides pattern recognition to the monitoring system for solvent manufacturing process and shows performance in real-time response with multiple input signals. Data is teamed by a multilayer feedforward network trained by error-backpropagation. The two kinds of test results show that the trained network has the ability to show the current system status with different input data sets.

• IE interfaces
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• v.19 no.1
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• pp.19-25
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• 2006

In the development process, the objective of a reliability growth program is to track the increase in system reliability, and determine as early as possible whether or not the system reliability is growing at a sufficient rate to meet the required goal and allocate available resources accordingly. Implementation of this kind of program will provide very useful information on concept selection, product/process reliability, and cost effectiveness without too much time, money and engineering effort being spent on the development of failure suspect parts. The purpose of this research is to present a practical method for efficiently monitoring a reliability growth test process using AMSAA(Army Materiel Systems Analysis Activity) reliability growth model. The presented growth management is a viable method for identifying failure modes, incorporating design changes and monitoring reliability progress on an on-going basis during the early stages of a product development program.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.250-252
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• 2002

The goals of environmental monitoring are to locate and quantify the significant contamination, estimate the fate and transport, estimate the potential exposure and risks to humans and the environment, and track the performance of various remedial technologies. In this study, ceramic gas sensor system is proposed to enhance the effectiveness of soil vapor extraction (SVE) process by monitoring the effluent gas. SVE is a technique that is widely used to remediate unsaturated soils contaminated with volatile organic contaminants. The sensor response for benzene, toluene, and xylene, the representative effluent gas compositions of SVE process, was evaluated using the proposed sensor system. As a result, it was verified that the response of sensor was increased or decreased very sensitively according to the change of the effluent gas concentration. Besides, the sensor could detect the difference over a wide range of concentration and it was more sensitive in order of xylene, toluene, and benzene. It is expected that this VOC analysis method results in field monitoring costs saying and appropriate immediate action for process control. More detailed experiments are being conducted in our research group.

• Journal of the Korea Society for Simulation
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• v.7 no.2
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• pp.137-152
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• 1998

One of the components that constitute the simulation models is the state variables whose values are determined by the time related simulation process. Embedding rule-based expert systems into the simulation models should provide a systematic way of handling these time-dependent variables without distracting the essential problem solving capabilities of the expert systems which are well suited for expressing the decision making function of complex cases. The expert system, however, is inefficient in dealing with the time elapsing characteristics of target system compare to the simulation models. To solve the problem, this paper provides an interruptible inference engine whose inferencing process can be interrupted when the variables' value, which are used as the parameters of the rules, are not yet determined due to the time dependent nature of the state variables. The process is resumed when the variables are ready. The elapse of time is calculated by time-advance function of the simulation model to which the expert system has been embedded. The example modeling shown exploits the embedded interruptible inferencing capability for the controlling and monitoring of metal grating process.