• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.5
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• pp.496-510
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• 2016

Simulation technology is a type of shipbuilding product lifecycle management solution used to support production planning or decision-making. Normally, most shipbuilding processes are consisted of job shop production, and the modeling and simulation require professional skills and experience on shipbuilding. For these reasons, many shipbuilding companies have difficulties adapting simulation systems, regardless of the necessity for the technology. In this paper, the data model for shipyard production simulation model generation was defined by analyzing the iterative simulation modeling procedure. The shipyard production simulation data model defined in this study contains the information necessary for the conventional simulation modeling procedure and can serve as a basis for simulation model generation. The efficacy of the developed system was validated by applying it to the simulation model generation of the panel block production line. By implementing the initial simulation model generation process, which was performed in the past with a simulation modeler, the proposed system substantially reduced the modeling time. In addition, by reducing the difficulties posed by different modeler-dependent generation methods, the proposed system makes the standardization of the simulation model quality possible.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.349-353
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• 2001

There are many excellent characters of Java-based simulation compared with existing ones in the respect of running on the Internet/Web, reuse, integration and etc.. In this paper, the main idea of design and realization of Java-based modeling and simulation software for DEVS will be discussed in detail.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.27-40
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• 2020

When analyzing the effectiveness of a defense system in a virtual battlefield with a simulation model is referred to as forward simulation, reverse simulation is required to design a good defense system with high effectiveness. That is, using the simulation model, it is necessary to find the engineering factors, measures of performance, and operational tactics that are demanded to achieve high effectiveness of the system. However, the efficiency of reverse simulation is still a concern since many replications of forward simulation are required for conducting reverse simulation. In this paper, we introduce various efficient algorithms to reduce the number of replications and a reverse simulation tool for utilizing these algorithms easily. The tool allows practitioners to easily and efficiently conduct reverse simulation for design a good defense system based on simulation models. This is demonstrated with the case studies on the design of warship's defense system and the design of military network system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.24-30
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• 2008

A simulation of hot strip finishing mill automatic gauge control (AGC) system is built, which is divided into four modules such as rolling mill system, AGC module, looper system and strip model. The rolling mill system is built by mechanism modeling, the looper system and strip model are built by function modeling, and the AGC model is tried to use intelligent control of a multi-function AGC system. The target is attempted to use this simulation object to minimize finisher exit strip thickness deviation resulting from strip entry thickness disturbance and rolling force deviation. Simulation results show that the result of this AGC/LPC synthetical system module simulation is quite close to the actual result. The simulation system can also analyze most kinds of disturbance which affect the rolling process. It is proved that the system can represent practical situation of hot strip finishing mill process control, and be used as a basic platform of research and development for researcher and engineer.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.136-148
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• 1995

In this study, a model integration method is pressented as a new method for development of a parametric simulation model. This method enable us to integrate the special simulation models for each production subsystem into a large simulation model. Not only this large simulation model but also each special simulation model for each production subsytem can be used independently. Using this integration method man can reduce the development time and cost for simulation model development. To show the usefulness of this method, a simulation model for a production system with robots is developed by this model integration method. This simulation model is realized by the integration of two special simulation models, one model for a machining subsystem and the other model for a transport subsystem. The modeled production system consists of the robotic cells for machining and a transport subsystem which enable the material flow among the robotic cells. The flow of workpiece in each robotic cell is not fixed. All machines in a robotic cell are only served by robots.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.2
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• pp.112-121
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• 2006

To evaluate the performance of ventilation system properly, the correlations among the ventilation rate, indoor air-quality and cooling/heating load should be analysed. In this study, simulation tool to analyze the performance of ventilation system was developed. The simulation tool is based on the TRNSYS and some modules to calculate concentration of pollutants with the operation of ventilation system and to decide the signal of ventilation system were newly developed in this study. And these modules coupled with building load and heating/cooling simulation modules. To verify the validity of developed simulation tool, comparison study between simulation and field study were accomplished. As results, the simulation tool developed in this study can be used to predict the performance of ventilation system with accuracy.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.20-37
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• 2020

In this paper, we propose a simulation method based on backward simulation and process-oriented simulation to take into account the characteristics of shipbuilding production, which is an order-based industry with a job shop production environment. The shipyard production planning process was investigated to analyze the detailed process, variables and constraints of mid-term production planning. Backward and process-centric simulation methods were applied to the mid-term production planning process and an improved planning process, which considers the shipbuilding characteristics, was proposed. Based on the problem defined by applying backward process-centric simulation, a system which can conduct Discrete Event Simulation (DES) was developed. The developed mid-term planning system can be linked with the existing shipyard Advanced Planning System (APS). Verification of the system was performed with the actual shipyard mid-term production data for the four ships corresponding to a one-year period.

• Korean System Dynamics Review
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• v.12 no.1
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• pp.115-130
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• 2011

This study shows the operational availability(Ao) analysis of the supply chain with maintenance functions using the system dynamics simulation. The simulation uses 60 equipments which are serial systems composed by 4 major components. And every entities are connected each other by causal loops. So whole simulation executed like one organic system. Specially we consider 2 constraints, one is the number of spare parts and the other is maintenance capacity level. 2 constraints have 11 levels each so the simulation has 121(11*11) scenarios which scenario has 30 different random number seed. The simulation executed total 3,630(11*11*30) times. We analysis average Ao of total equipments by 121 scenarios and additionally the regression of the average Ao and 2 constraints. As the result, we can get the more accurate values by the system dynamics simulation than the regression to analysis complex system like the supply chain with maintenance functions.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.6
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• pp.845-851
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• 1986

This Paper presents micro-computer simulation programs for a pneumatic control system. The simulation programs have been written in BASIC language which is suitable for 6502CPU with 48KB memory and consist of 11 programs which describe the time response and frequency response of the pneumatic actuation system. This simulation package is stored in 51/4 inch floppy diskette. The user requires no simulation expertise on the part of designer. As the result of using this simulation programs for the pneumatic control system with stabilizing tank, it has shown that the response time of the system using air as working medium takes more time to be settled but relatively stable rather than the system using helium.