• 한국정밀공학회지
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• 제22권6호
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• pp.135-143
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• 2005

The shoes process management monitoring system for supporting SCM is developed in this study. This system consists of a monitoring program, a conveyer system, a pneumatic unit, a controller, an USB camera, and a server and a client computer. To operate the developed system easily, the monitoring program using LabVIEW in the Windows environment is developed. This program consists of 5 modules: production management, inventory control, media management, defective management, and communication management. The developed system has several advantages: reduced time for managing process work, decreased labor costs, effective operation, and continuous work without an operator. Nowadays advanced manufacturing companies are trying to find a way to check the performance of their production equipments and plants from remote sites. Thus, to manage the developed system from remote sites, communication network is constructed. In order to evaluate the performance of the monitoring system, experiments were performed. The experimental results showed that the developed system provided a reliable performance and a stable communication.

• 산업경영시스템학회지
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• 제17권32호
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• pp.145-154
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• 1994

In this paper, monitoring processor in a circuit switched network is considered. Monitoring processor monitors communication links, and offers a grade of service in each link to controller. Such an information is useful for an effective maintenance of system. Two links with nonsymmetric system Parameters are considered. each link is assumed independent M/M/1/1 type. The Markov process is introduced to compute busy and idle portions of monitoring processor and monitored rate of each link. Inter-idle times and inter-monitoring times of monitoring processor between two links are respectively computed. A recursive formula is introduced to make computational procedure rigorous.

• 동력기계공학회지
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• 제4권2호
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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.

• 한국산학기술학회논문지
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• 제8권5호
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• pp.1082-1086
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• 2007

본 연구는 국내에서 발생되는 소각재를 재활용하여 벽돌 생산을 하는 공장에서의 이원화된 작업현황을 일원화 할 수 있는 데이터 모니터링 시스템 구축을 목적으로 한다. 모니터링 시스템은 상태관리 프로세스, 위치관리 프로세스, 불량관리 프로세스, 상황관리 프로세스 등의 데이터 관리 프로세스를 이용해 데이터를 자동 관리하도록 설계하였다. 본 연구에서는 RFID 태그를 이용하여 각 공정의 상황 정보를 수집하고 수집된 정보를 가공하여 데이터 모니터링 시스템에 전송한다. 이러한 시스템을 통해 분석된 데이터는 소각재를 재활용하여 벽돌 생산을 하는 공장에서 공정자동화, 불량률 최소화, 실시간 모니터링, 적재 관리를 통해 생산 공정을 효율적으로 관리할 수 있다.

• 산업경영시스템학회지
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• 제31권1호
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• pp.92-100
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• 2008

This paper develops a process monitoring system for real-time process control. The practical case is studied on a small and medium marine equipment company. For business process reengineering of the company, we adopt an approach based on information engineering methodology, which consists of four stages : planning, analysis, design, and implementation. The system is developed for Client/Server environment. We discuss the constructing of hardware system for real-time process control at low cost. The developed system is composed of interrelated modules for item master and BOM management, process control, facility management, SQC and work report.

• 한국기계가공학회지
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• 제11권5호
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• pp.142-147
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• 2012

Machining tool conditions directly affect to quality of product and productivity of manufacturing. Many researches performed for tool condition monitoring in machining process to improve quality and productivity. Conventional methods use characteristics of signal for cutting force, motor current consumption, vibration of machine tools and machining sound. Recently, diameter of machining tool is become smaller for minimizing of mechanical parts. Tool condition monitoring using conventional methods are relatively difficult because micro machining using small diameter tool has low machining load and high cutting speed. These days, the direct monitoring for tool conditions using vision system is performed actively. But, vision system is affected by external conditions such as back ground of image and illumination. In this study, minimizing technology of external conditions using distribution analysis of image data are developed in micro machining using small diameter drill and tap. The image data is gathered from vision system. Several sets of experiment results are performed to verify the characteristics of the proposed machining technology.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.105.4-105
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• 2001

This paper describes a newly designed multipoint process monitoring system based on a NIR acousto-optic tunable filter. The NIR multipoint process monitoring system consists of a NIR AOTF device for wavelength selection, an InGaAs array sensor, and a specially designed iin-line type of optical fiber probe. Unlike a FTS(Fourier Transform Spectrometry) or grating based monitoring system, an AOTF has no moving parts, and it can be rapidly tuned to any wavelength in its operating range within microseconds. Thus, the AOTF is advantageous in terms of faster spectral imaging capability and rigidity required for industrial monitoring environment. In the current feasibility evaluation, an enhanced optical fiber probe with 3 monitoring points was used. However, ...

• 한국정밀공학회지
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• 제13권9호
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• pp.149-155
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• 1996

Recent researches in the trouble monitoring system of grinding process have emphasized the use of deep knowledge. Such works include the monitoring and diagnostic systems for cylindrical grinding using sensors on chatter vibration and grinding burn during the process. But, since grinding operations are especially related with a lalrge amount of ambique parameters, it is effectively difficult to detect the grinding troubles occuring during the grinding process. In this paper, monitoring system for grinding utilizes the neural networks based on grinding power signatures. The monitoring system of grinding operations, which makes use of PDP neural networks, is presented. Then, the implementation results by computer simulations and experimental data with respect to chatter vibration and grinding burn are compared.

• 한국경영과학회지
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• 제36권1호
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• pp.39-55
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• 2011

Process monitoring has been emphasized for the monitoring of complex system such as chemical processing industries to achieve the efficiency enhancement, quality management, safety improvement. Recently, ICA (Independent Component Analysis) based MSPC (Multivariate Statistical Process Control) was widely used in process monitoring approaches. Moreover, DICA (Dynamic ICA) has been introduced to consider the system dynamics. However, the existing approaches show the limitation that their performances are strongly dependent on the statistical distributions of control variables. To improve the limitation, we propose a novel approach for process monitoring by integrating DICA and LOF (Local Outlier Factor). In this paper, we aim to improve the fault detection rate with the proposed method. LOF detects local outliers by using density of surrounding space so that its performance is regardless of data distribution. Therefore, the proposed method not only can consider the system dynamics but can also assure robust performance regardless of the statistical distributions of control variables. Comparison experiments were conducted on the widely used benchmark dataset, Tennessee Eastman process (TE process), and showed the improved performance than existing approaches.

• 한국공작기계학회논문집
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• 제11권3호
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• pp.39-44
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• 2002

As laser cutting process is widely used in industry, an automated on-line process control system has become very important. In this paper, development of a laser cutting monitoring system, which is regarded as the fundamental step toward automation of the process, is presented. Acoustic emission and an artificial neural network were used for the monitoring system. With given process Parameters including laser power and scanning speed the system can predict the suitability of laser beam for the cutting or a stainless steel (STS304) plate.