• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.1-11
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• 2023

Smart factory environments and digital twin environments are established, and today's factories accumulate vast amounts of production data and are managed in real time as visualized results suitable for user convenience. Production simulation techniques are in the spotlight as a way to prevent delays in delivery and predict factory volatility in situations where production schedule planning becomes difficult due to the diversification of production products. With the development of the digital twin environment, new packages are developed and functions of existing packages are updated, making it difficult for users to make decisions on which packages to use to develop simulations. Therefore, in this study, the concept of Discrete Event Simulation (DES) performed based on discrete events is defined, and the characteristics of various simulation packages were compared and analyzed. To this end, studies that solved real problems using discrete event simulation software for 10 years were analyzed, and three types of software used by the majority were identified. In addition, each package was classified by simulation technique, type of industry, subject of simulation, country of use, etc., and analysis results on the characteristics and usage of DES software were provided. The results of this study provide a basis for selection to companies and users who have difficulty in selecting discrete event simulation package in the future, and it is judged that they will be used as basic data.

• Proceedings of the Korea Society for Simulation Conference
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• 1996.05a
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• pp.15-15
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• 1996

A shop floor control system (SFCS) is the central part of a CIM system used to control the activities of several pieces of manufacturing equipment (e.g., NC machines, robots, conveyors, AGVs, AS/RS). The SFCS receives orders and related process plans, and then performs selecting a specific process routing, allocating resources, scheduling the workpieces, downloading the processing instructions (e.g., RS-274 instructions for NC machines, VAL II programs for robot), monitoring the progress of activities, detecting and recovering from errors, and preparing reports on the status of the manufacturing system. Simulation has been utilized in discovering control policies used for resolving shop floor be control problems such as resource contentions, part dispatching, deadlock. The simulation model must be designed to respond to real-time data coming from a shop floor. However, to rapidly build a realtime simulation model of SFCS cannot be easily accomplished. This talk is to address an automatic program generator of discrete event simulation model for shop floor control from process plans and resource models. The program generator is capable of constructing complete discrete simulation models for multi-product and multi-stage flexible manufacturing systems.

• Journal of the Korea Society for Simulation
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• v.24 no.2
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• pp.1-9
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• 2015

The tactical employment is a critical factor to win the war in the modern battlefield. To apply optimized tactics, it needs analyses related to a battle system. Normally, M&S (Modeling & Simulation) has been studied to analyze data in general problems. However, this method is not suitable for military simulations because there are many variables which make complex interaction in the system. For this reason, we suggested the optimized simulation framework based on the M&S by using DPSO (Discrete binary version of PSO) algorithm. This optimized simulation framework makes the best tactical employment to reduce the searching time compared with the normal M&S used by Monte Carlo search method. This paper shows an example to find the best combination of anti-torpedo scenario in a short searching time. From the simulation example, the optimized simulation framework presents the effectiveness.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.53-63
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• 2018

In this paper, we analyze the waiting time of a queueing system with D-BMAP (discrete-time batch Markovian arrival process) and D-policy. Customer group or packets arrives at the system according to discrete-time Markovian arrival process, and an idle single server becomes busy when the total service time of waiting customer group exceeds the predetermined workload threshold D. Once the server starts busy period, the server provides service until there is no customer in the system. The steady-state waiting time distribution is derived in the form of a generating function. Mean waiting time is derived as a performance measure. Simulation is also performed for the purpose of verification and validation. Two simple numerical examples are shown.

• 전기의세계
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• v.30 no.12
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• pp.822-831
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• 1981

Many different schemes of the adaptive observer and controller have been developed for both continuous and discrete systems. In this paper we have presented a new scheme of the reduced order adaptive observer for the single input discrete linear time invariant plant. The output equation of the plant, is transformed into the bilinear form in terms of system parameters and the states of the state variable filters. Using the plant output equation the discrete implicit adaptive observer based on the similar philosophy to Nuyan and Carroll is derived and the parameter adaptation algorithm is derived based on the exponentially weighted least square method. The adaptive model following control system is also constructed according to the proposed observer scheme. The proposed observer and controller are rather than simple structure and have a fast adaptive algorithm, so it may be expected that the scheme is suitable to the practical application of control system design. The effectiveness of the algorithm and structure is illustrated by the computer simulation of a third order system. The simulation results show that the convergence speed is proportinal to the increasing of weighting factor alpha, and that the full order and reduced order observer have similar convergence characteristics.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.543-547
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• 2004

Visualization of construction process simulation and physical modeling were considered to overcome the limitations of current graphical simulation. The output of discrete-event simulation programs which are the most common mathematical statistical simulation tool for construction processes were analyzed for the visualization of earthmoving process that dealing with objects without fixed. Object-oriented models for equipment, material and work environments were devised to effectively visualize the numerical simulation results of the working time, the queuing time as well as the amount resources etc. The oscillation of the crane's cable and the lifted material that should be considered to rationally modeled and simulated by construction graphical simulation. The derived equation of motion was solved by numerical analysis procedure. Then obtained results was used for physical modeling.

• Wind and Structures
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• v.18 no.3
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• pp.215-233
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• 2014

This paper presents a method to extract flutter derivatives of bridge decks based on a combination of the computational fluid dynamics (CFD), system simulations and system identifications. The incompressible solver adopts an Arbitrary Lagrangian-Eulerian (ALE) formulation with the finite volume discretization in space. The imposed sectional motion in heaving or pitching relies on exponential time series as input, with aerodynamic forces time histories acting on the section evaluated as output. System identifications are carried out to fit coefficients of the inputs and outputs of ARMA models, as to establish discrete-time aerodynamic models. System simulations of the established models are then performed as to obtain the lift and moment exerting on the sections to a sinusoidal displacement. It follows that flutter derivatives are identified. The present approaches are applied to a hexagon thin plate and a real bridge deck. The results are compared to the Theodorsen closed-form solution and those from wind tunnel tests. Satisfactory agreements are observed.

• Nuclear Engineering and Technology
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• v.21 no.3
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• pp.223-230
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• 1989

This paper describes dynamic simulation of the spent fuel storage system which is described by statistical discrete event models. It visualizes flow and queue of system over time, assesses the operational performance of the system acitivies and establishes the system components and streams. It gives information on system organization and operation policy with reference to the design. System was tested and analyzed over a number of critical parameters to establish the optimal system. Workforce schedule and resources with long processing time dominate process. A combination of two workforce shifts a day and two cooling pits gives the optimal solution of storage system. Discrete system simulation is an useful tool to get information on optimal design and operation of the storage system.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.478-485
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• 2000

A discrete event systems (DES) is a physical system that is discrete in time and state space, asynchronous (event rather than clock-driven), and in some sense generative(or nondeterministic). This paper presents the design of fifteen modular supervisors to control an experimental CIM testbed. These supervisors are nonblocking, controllable and nonconflicting. After verification of the supervisors by simulation, the supervisors for AGV system have been implemented to demonstrate their efficacy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.452-474
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• 2010

Formidable growth of Internet technologies has revealed challenging issues about its scale and performance evaluation. Modeling and simulation play a central role in the evaluation of the behavior and performance of the large-scale network systems. Large numbers of nodes affect simulation performance, simulation execution time and scalability in a weighty manner. Most of the existing simulators have numerous problems such as size, lack of system theoretic approach and complexity of modeled network. In this work, a scalable discrete-event modeling approach is described for studying networks' scalability and performance traits. Key fundamental attributes of Internet and its protocols are incorporated into a set of simulation models developed using the Discrete Event System Specification (DEVS) approach. Large-scale network models are simulated and evaluated to show the benefits of the developed network models and approaches.