Arena Simulation Tool Research Articles

Simulation model of natural gas supply chain in a function of costs optimization: the case of Croatia

The purpose of this study is to develop a natural gas simulation model for costs optimization. The main focus of the model is on the transmission system since its imbalance leads to the penalties which must be paid by the suppliers. The total nominated amount of natural gas (the gas injected into the transmission system) must be consumed (withdrawn from the system) in order for the system to be in balance. In practice, this is not the case since it is very hard to accurately predict the future hourly consumption (in order to make a nomination) and certain deviations appear which leads to the imbalance. However, this problem could be solved by introducing a special electromotor valve which would be placed at the beginning of the distribution system and control the accumulation of the system. To test this solution, a simulation model was created using Arena Simulation tool. Data for the simulation model are collected by the natural gas distributor and consist of natural gas consumption and nomination values for one measuring-reduction station on the hourly basis. Thus, the final dataset includes 8.754 records. The separate As-Is and To-Be models for seven (summer) months were made and the results were compared. The simulation experiment shows that the positive rebalancing energy would be reduced by 32%, and the negative one by 34%. The created model can serve as a good initial step for the analysis of the justification of investment in the implementation of a technical solution that would manage the accumulation of the distribution system.

모바일 사물인터넷 기반 자동심장충격기 효과 측정을 위한 시뮬레이션 분석

In this paper, we report the process changes and quantitative benefit analysis result when mobile IoT technology is embedded into AED(Automated External Defibrillator) for the emergency heart attack patients. To-be process change versus as-is stand-alone AED is illustrated based on BPMN(Business Process Model and Notation) standard, and ARENA simulation tool is adopted to assess the benefit as for the possible multiple to-be process scenarios. We reference the actual data collected from Centers for Disease Control and Public Data Portal to develop to-be scenarios and simulation modeling. The lead time to dispatch the emergent patients to the hospital, CPR(cardiopulmonary resuscitation) treatment percentage, and survival rate are revealed to be radically improved, which are the benefit accrued by the implementation of mobile IoT based AED. The research result offers useful insight for the recently propagating mobile IoT based business model design and expected benefit analysis.

Comparison of Anomaly Detection Accuracy of Host-based Intrusion Detection Systems based on Different Machine Learning Algorithms

Among the different host-based intrusion detection systems, an anomaly-based intrusion detection system detects attacks based on deviations from normal behavior; however, such a system has a low detection rate. Therefore, several studies have been conducted to increase the accurate detection rate of anomaly-based intrusion detection systems; recently, some of these studies involved the development of intrusion detection models using machine learning algorithms to overcome the limitations of existing anomaly-based intrusion detection methodologies as well as signature-based intrusion detection methodologies. In a similar vein, in this study, we propose a method for improving the intrusion detection accuracy of anomaly-based intrusion detection systems by applying various machine learning algorithms for classification of normal and attack data. To verify the effectiveness of the proposed intrusion detection models, we use the ADFA Linux Dataset which consists of system call traces for attacks on the latest operating systems. Further, for verification, we develop models and perform simulations for host-based intrusion detection systems based on machine learning algorithms to detect and classify anomalies using the Arena simulation tool.

Measuring the Performance of Inventory Management System using Arena Simulator

The demonstration of inventory management systems is presented in this study to deal with a situation, where organizations are facing challenges due to uncertain behavior of demand. The implementation conducted using simulation technique to generate sampling experiment through computing and statistical methods. The important aspect of the simulation is to understand level of satisfaction regarding proposed system and its attributes. To assist the organization in controlling and managing the inventory system, the research provides the solution using Arena simulation tool. Firstly, the study explained the use of simulation and then reviews the common approaches of simulation. Secondly, the research proposed a framework for inventory control system. For practical implementation Arena tool used for model implementation. The main purpose of this experiment is to measure and analyze the applicability of potential system using a simulation tool. The results indicated the successful implementation of the proposed framework for inventory system. The model used multiple inventory system’s variables such as demand, inventory stock and realized cost. For demonstrating the real world system’s behavior, we used stochastic model for demand. The model executed using single server queuing (M/M/1) approach, but replicated several times. The results highlighted the high performances of machine located on multiples places and processed demand requests on each replication run. The study presented in this research demonstrates the association between demand and inventory. The proposed model can support the manufacturing organizations to control and manage inventory system.

A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS. The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.

차세대 함정 전투체계 아키텍처 구축방안에 관한 연구

A naval combat system is the system of systems who supports naval indigenous operations by integrating and inter-operating many different kind of weapons, which has characteristics of large scale complex computing system. ROK Navy has been built a blue ocean navy, so that large scale warships are under constructions. However, warship combat system architecture has not been well studied so far in Korea. The paper focuses on current combat system architecture and propose the next generation combat system architecture, which will give the development direction of ROK Navy. In order to complete combat system architecture studies, the system engineering process shall be applied to the study. Moreover, ARENA simulation tool is used for verification of combat system architecture. The system engineering process is as follows: next-generation naval combat system requirement analysis, functional architecture analysis and physical architecture analysis.

UML Profile for Mining Process: Supporting Modeling and Simulation Based on Metamodels of Activity Diagram

An UML profile describes lightweight extension mechanism to the UML by defining custom stereotypes, tagged values, and constraints. They are used to adapt UML metamodel to different platforms and domains. In this paper we present an UML profile for models supporting event driving simulation. In particular, we use the Arena simulation tool and we focus on the mining process domain. Profiles provide an easy way to obtain well-defined specifications, regulated by the Object Management Group (OMG). They can be used as a presimulation technique to obtain solid models for the mining industry. In this work we present a new profile to extend the UML metamodel; in particular we focus on the activity diagram. This extended model is applied to an industry problem involving loading and transportation of minerals in the field of mining process.

Modeling and Simulation of Urban Traffic Signals

Traffic signals play a vital role in effective traffic management. In this paper we apply Arena simulation tool box for modeling and simulation of urban traffic signal system. It has been shown that Arena could be used in simulation of traffic signals system, despite the fact that Arena is not designed for modeling urban traffic signal control. We presented a non-trivial case study to illustrate how Arena is capable of modeling traffic systems.

A GIS‐based Approach in Support of an Assessment of Food Safety Risks

AbstractA Geographical Information System (GIS)‐based approach was developed for the identification of vulnerabilities and the measurement of risks associated with contamination of food systems with biological agents. In this research work, a tight integration of ArcGIS with the Arena simulation tool has been implemented. Arena was used to simulate and track contamination in a food distribution network and transmit the time dependent information to GIS. ArcGIS was employed to provide the primary user interface, process network data, and visualize the results. In addition, the GIS, through its powerful capabilities to process spatial data, could allow decision‐ makers to quickly determine the potential impact of a contamination event, at any stage, as a function of both time and geography. Two contamination scenarios along the farm‐to‐fork chain were examined to show the geographic zone and the proportion of the population affected by the contamination. A constraint Voronoi data structure was developed to define influence zones (these were color coded according to a dynamic risk index), to identify those areas that are at greatest immediate risk as time progresses, and to estimate the population affected by these contamination events. This approach thus appears to have general application to many GIS‐based risk assessment problems.