• Journal of The Korean Association of Information Education
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• v.15 no.1
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• pp.111-117
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• 2011

Many various researches about the PC execution process monitoring system have studied. Nevertheless, it is hard to find research of a system that multi-PC based each PC can be monitoring and reporting by file type. In this study, it designed and implemented that each PC can be monitoring and reporting by files to a server in multi-PCs' environments. Moreover it can gather and organize informations of reporting. It is expected users can recognize that execution processes are reporting. It causes to reduce execution unnecessary process.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.21-31
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• 2010

A manufacturing execution system in the process according to automation system of installation management has been growing interest about effective system design and effective system manage. In this paper, we propose an ubiquitous Manufacturing Execution System based on RFID/USN for checkup monitoring and history management of installation in manufacturing execution systems. For this, we design and implement installation history and statistics management system based on RFID grafting RFID for efficient installation equipment history and statistics management of ubiquitous Manufacturing Execution System, and was implemented checkup monitoring system based on USN using temperature sensor, humidity sensor, hydraulic pressure sensor for failure prevention of ubiquitous Manufacturing Execution System. And proposed ubiquitous Manufacturing Execution System is implemented based on JSP for access through Web in real time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1016-1019
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• 1996

This paper discribes automobile processes and introduction for process monitoring and control system for engine plant, truck automobile industries using the MES(Manufacturing Execution Systems) functions.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1074-1081
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• 2011

As robotics systems are becoming more complex there is the need to promote component based robot development, where systems can be constructed as the composition and integration of reusable building block. One of the most important challenges facing component based robot development is safeguarding against software component failures and malfunctions. The health monitoring of the robot software is most fundamental factors not only to manage system at runtime but also to analysis information of software component in design phase of the robot application. And also as a lot of monitoring events are occurred during the execution of the robot software components, a simple data treatment and efficient memory management method is required. In this paper, we propose an efficient events monitoring and data management method by modeling robot software component and monitoring factors based on robot software framework. The monitoring factors, such as component execution runtime exception, Input/Output data, execution time, checkpoint-rollback are deduced and the detail monitoring events are defined. Furthermore, we define event record and monitor record pool suitable for robot software components and propose a efficient data management method. To verify the effectiveness and usefulness of the proposed approach, a monitoring module and user interface has been implemented using OPRoS robot software framework. The proposed monitoring module can be used as monitoring tool to analysis the software components in robot design phase and plugged into self-healing system to monitor the system health status at runtime in robot systems.

• Korean Management Science Review
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• v.21 no.3
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• pp.115-127
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• 2004

In this paper, we describe an intelligent monitoring and control system for pick-up/delivery service. This system applies geographical information system(GIS), global positioning system(GPS) and wireless communication technologies for managing pick-up/delivery operations more effectively. It consists of three subsystems, pick-up/delivery sequence planning system, pick-up/delivery monitoring system, and PDA execution system. Pick-up/delivery sequence planning system generates routes and schedules for pick-up/delivery using GIS and optimization techniques. Pick-up/delivery monitoring system monitors current positions of vehicles and actual pick-up/delivery results as compared with planned routes and visit times, while PDA execution system transmits information for vehicles positions and actual pick-up/delivery results using GPS and wireless communication technologies. The intelligent monitoring and control system is currently being used for the pick-up parcel service in a local post office of Korea Post.

• The KIPS Transactions:PartA
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• v.13A no.3 s.100
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• pp.205-210
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• 2006

To assist developing robust multithreaded software, we develop a thread monitoring system for multithreaded Java programs, which can trace or monitor running threads and synchronization. We design a monitoring system which has options to select interesting threads and synchronizations. Using this tool, programmers can monitor only interesting threads and synchronization in more details by selecting options. It also provides profile information after execution, which summarizes behavior of running threads and synchronizations during execution. We implement the system based on code inlining, and presents some experimental results.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.97-106
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• 2007

In this paper, the business process was easily modeled by distinguishing between the business process and work logic. Based on this model, B2Bi collaboration Workflow modeling tool, which facilitates collaboration, was designed and implemented. The collaboration workflow modeling tool consists of 3 components; business process modeling tool, execution engine and monitoring tool. First, a business process modeling tool is used to build a process map that reflects the business logic of an application in a quick and accurate manner. Second an execution engine provides a real-time execution environment for business process instance. Third, a monitoring tool provides a real-time monitoring function for the business process that is in operation at the time. In addition to this, it supports flexibility and expandability based on XML and J2EE for the linkage with the legacy system that was used previously, and suggests a solution for a new corporate strategy and operation.

• Journal of Navigation and Port Research
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• v.34 no.7
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• pp.595-601
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• 2010

This paper aims to diagnose the strategy execution ability and to provide corresponding measures for Korean oceanic shipping companies. The analysis method is the t-test between importance awareness and Corresponding ability for strategy execution diagnosis index(XPP). According to the diagnosed results, the strategy development is unsatisfactory because the strategy implemented does not adhere to concurrent environmental change. Moreover, the execution of the strategy is also unsatisfactory. Therefore, an evaluation shows that there is a need for a SWOT analysis using BSC, an organization structure to strengthen the strategy execution ability and the support from the market condition analysis prediction center.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.17-18
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• 2008