scholarly journals The Use of Simulation Models in Solving the Problems of Merging two Plants of the Company

2017 ◽  
Vol 7 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Michal Sedláček

AbstractThis paper focuses on utilization of analysis of different possibilities of merging two production sites with the help of simulation model of company processes. Software SIMUL8 was chosen as a development environment for its possibility of dynamic discrete simulation of company processes. In the first phase, it analyses current status of both production sites. It is followed by suggesting several possible solutions for their potential merger. Each solution is analyzed with the help of simulation models. They have been evaluated and the optimal solution was selected.

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Alexander I. Kozynchenko ◽  
Sergey A. Kozynchenko

The paper mostly focuses on the methodological and programming aspects of developing a versatile desktop framework to provide the available basis for the high-performance simulation of dynamical models of different kinds and for diverse applications. So the paper gives some basic structure for creating a dynamical simulation model in C++ which is built on the Win32 platform with an interactive multiwindow interface and uses the lightweight Visual C++ Express as a free integrated development environment. The resultant simulation framework could be a more acceptable alternative to other solutions developed on the basis of commercial tools like Borland C++ or Visual C++ Professional, not to mention the domain specific languages and more specialized ready-made software such as Matlab, Simulink, and Modelica. This approach seems to be justified in the case of complex research object-oriented dynamical models having nonstandard structure, relationships, algorithms, and solvers, as it allows developing solutions of high flexibility. The essence of the model framework is shown using a case study of simulation of moving charged particles in the electrostatic field. The simulation model possesses the necessary visualization and control features such as an interactive input, real time graphical and text output, start, stop, and rate control.


Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 242
Author(s):  
Christoph Schünemann ◽  
David Schiela ◽  
Regine Ortlepp

Can building performance simulation reproduce measured summertime indoor conditions of a multi-residential building in good conformity? This question is answered by calibrating simulated to monitored room temperatures of several rooms of a multi-residential building for an entire summer in two process steps. First, we did a calibration for several days without the residents being present to validate the building physics of the 3D simulation model. Second, the simulations were calibrated for the entire summer period, including the residents’ impact on evolving room temperature and overheating. As a result, a high degree of conformity between simulation and measurement could be achieved for all monitored rooms. The credibility of our results was secured by a detailed sensitivity analysis under varying meteorological conditions, shading situations, and window ventilation or room use in the simulation model. For top floor dwellings, a high overheating intensity was evoked by a combination of insufficient use of night-time window ventilation and non-heat-adapted residential behavior in combination with high solar gains and low heat storage capacities. Finally, the overall findings were merged into a process guideline to describe how a step-by-step calibration of residential building simulation models can be done. This guideline is intended to be a starting point for future discussions about the validity of the simplified boundary conditions which are often used in present-day standard overheating assessment.


2013 ◽  
Vol 309 ◽  
pp. 366-371 ◽  
Author(s):  
František Manlig ◽  
Radek Havlik ◽  
Alena Gottwaldova

This paper deals with research in computer simulation of manufacturing processes. The paper summarizes the procedures associated with developing the model, experimenting with and evaluating the model results. The key area is of experimentation with the simulation model and evaluation using indicators or multi-criteria functions. With regards to the experiment the crucial variables are the simulation model. The key ideas are to set the number of variables, depending on what a given simulation will be. For example, when introducing new technology into production, modify the type of warehouse, saving workers, thus economizing. The simulation models for the operational management uses simplified models, if possible, a minimum number of variables to obtain the result in shortest possible time. These models are more user friendly and the course will be conducted mostly in the background. An example of a criteria function is the number of parts produced or production time. Multi-criteria function has given us the opportunity to make better quality decisions. It is based on the composition of several parameters, including their weight to one end point. The type of evaluation functions, whether it is an indicator or criteria function is selected and based on customer requirements. In most cases it is recommended to use the multi-dimensional function. It gives us a more comprehensive view of the results from the model and facilitates decision-making. The result of this paper is a display of setting parameters for the experimentation on a sample model. Furthermore, the comparisons of results with a multi-criteria objective function and one-criterion indicator.


Author(s):  
Mahyar Asadi ◽  
Ghazi Alsoruji

Weld sequence optimization, which is determining the best (and worst) welding sequence for welding work pieces, is a very common problem in welding design. The solution for such a combinatorial problem is limited by available resources. Although there are fast simulation models that support sequencing design, still it takes long because of many possible combinations, e.g. millions in a welded structure involving 10 passes. It is not feasible to choose the optimal sequence by evaluating all possible combinations, therefore this paper employs surrogate modeling that partially explores the design space and constructs an approximation model from some combinations of solutions of the expensive simulation model to mimic the behavior of the simulation model as closely as possible but at a much lower computational time and cost. This surrogate model, then, could be used to approximate the behavior of the other combinations and to find the best (and worst) sequence in terms of distortion. The technique is developed and tested on a simple panel structure with 4 weld passes, but essentially can be generalized to many weld passes. A comparison between the results of the surrogate model and the full transient FEM analysis all possible combinations shows the accuracy of the algorithm/model.


Author(s):  
Dheeraj Agarwal ◽  
Linghai Lu ◽  
Gareth D. Padfield ◽  
Mark D. White ◽  
Neil Cameron

High-fidelity rotorcraft flight simulation relies on the availability of a quality flight model that further demands a good level of understanding of the complexities arising from aerodynamic couplings and interference effects. One such example is the difficulty in the prediction of the characteristics of the rotorcraft lateral-directional oscillation (LDO) mode in simulation. Achieving an acceptable level of the damping of this mode is a design challenge requiring simulation models with sufficient fidelity that reveal sources of destabilizing effects. This paper is focused on using System Identification to highlight such fidelity issues using Liverpool's FLIGHTLAB Bell 412 simulation model and in-flight LDO measurements from the bare airframe National Research Council's (Canada) Advanced Systems Research Aircraft. The simulation model was renovated to improve the fidelity of the model. The results show a close match between the identified models and flight test for the LDO mode frequency and damping. Comparison of identified stability and control derivatives with those predicted by the simulation model highlight areas of good and poor fidelity.


1992 ◽  
pp. 285-297
Author(s):  
Alan S. Goldfarb ◽  
Arlene R. Wusterbarth ◽  
Patricia A. Massimini ◽  
Douglas M. Medville

Author(s):  
Luigi Bottecchia ◽  
Pietro Lubello ◽  
Pietro Zambelli ◽  
Carlo Carcasci ◽  
Lukas Kranzl

Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open source energy system models, it has emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system that is used to reproduce and understand its behaviour under given conditions, without seeking an optimal solution. Given the lack of simulation models that are also fully open source, in this paper a new open source energy system model is presented. The developed tool, called Multi Energy Systems Simulator (MESS), is a modular, multi-node model that allows to investigate non optimal solutions by simulating the energy system. The model has been built having in mind urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be be represented as well. MESS is capable of performing analysis on systems composed by multiple energy carriers (e.g. electricity, heat, fuels). In this work, the tool’s features will be presented by a comparison between MESS itself and an optimization model, in order to analyze and highlight the differences between the two approaches, the potentialities of a simulation tool and possible areas for further development.


2021 ◽  
Vol 15 (4) ◽  
pp. 518-523
Author(s):  
Ratko Stanković ◽  
Diana Božić

Improvements achieved by applying linear programming models in solving optimization problems in logistics cannot always be expressed by physically measurable values (dimensions), but in non-dimensional values. Therefore, it may be difficult to present the actual benefits of the improvements to the stake holders of the system being optimized. In this article, a possibility of applying simulation modelling in quantifying results of optimizing cross dock terminal gates allocation is outlined. Optimal solution is obtained on the linear programming model by using MS Excel spreadsheet optimizer, while the results are quantified on the simulation model, by using Rockwell Automation simulation software. Input data are collected from a freight forwarding company in Zagreb, specialized in groupage transport (Less Than Truckload - LTL).


2021 ◽  
Vol 2125 (1) ◽  
pp. 012051
Author(s):  
Guoqing Qiu ◽  
Kedi Jiang ◽  
Shengyou Xu ◽  
Xin Yang ◽  
Wei Wang

Abstract Although the superior performance of SiC MOSFET devices has beenvalidated by many studies, it is necessary to overcome many technical bottlenecks to make SiC MOSFET gradually replace Si-based power devices into the mainstream. In view of the current situation where the performance of SiC MOSFETs in power conversion devices cannot be evaluated well at this stage, it is necessary to carry out fine modeling of SiC MOSFETs and establish accurate simulation models. In this paper, the powerful mathematical processing capability and rich modules of Matlab/Simulink are used to build a SiC MOSFET model, and then the product data sheet is compared with the fitted data. The results show that the switching simulation waveforms are in general agreement with the data sheet waveforms, and the error is less than 7%. Verifing the accuracy of the model and reducing the difficulty of modeling, it provides a new idea for establishing the circuit simulation model of SiC MOSFET in Matlab/Simulink.


2020 ◽  
Vol 70 (1) ◽  
pp. 54-59
Author(s):  
Zhi Zhu ◽  
Yonglin Lei ◽  
Yifan Zhu

Model-driven engineering has become popular in the combat effectiveness simulation systems engineering during these last years. It allows to systematically develop a simulation model in a composable way. However, implementing a conceptual model is really a complex and costly job if this is not guided under a well-established framework. Hence this study attempts to explore methodologies for engineering the development of simulation models. For this purpose, we define an ontological metamodelling framework. This framework starts with ontology-aware system conceptual descriptions, and then refines and transforms them toward system models until they reach final executable implementations. As a proof of concept, we identify a set of ontology-aware modelling frameworks in combat systems specification, then an underwater targets search scenario is presented as a motivating example for running simulations and results can be used as a reference for decision-making behaviors.


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