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Implementing and Introducing Simulation
Published in Andrew Greasley, Simulation Modelling, 2023
Historically DES systems were built using general-purpose computer languages, such as FORTRAN, C and C++. Later, languages such as Java were employed, and there are also implementations using the Visual Basic for Applications (VBA) language to employ the method on a spreadsheet platform. There are also a number of specialist computer languages developed specifically for constructing DES models, including SIMAN, SIMSCRIPT, SLAM and GPSS. However, for most applications for decision-making in an organisational setting, the use of Windows-based software, sometimes referred to as Visual Interactive Modelling systems (VIMS), is employed. These software packages include Arena, Simio, AnyLogic, Witness, Simul8 and the Tecnomatix Plant Simulation. These packages are based on the use of graphic symbols or icons which reduce or eliminate the need to code the simulation model. A model is instead constructed by placing simulation icons on the screen which represent different elements of the model. Data is entered into the model by clicking with a mouse on the relevant icon to activate a screen input dialog box. Animation facilities are also incorporated into these packages. For most business applications, these systems are the most appropriate, although the cost of the software package can be high. These systems use graphical facilities to enable fast model development and animation facilities. However, these systems do not release the user from the task of understanding the building blocks of the simulation system or understanding statistical issues.
Basic Algorithms and Software for the Layout Problem
Published in Sunderesh S. Heragu, Facilities Design, 2022
Plant Simulation interfaces with FactoryCAD and FactoryFLOW and can be used to develop a detailed simulation model so that a given layout can be evaluated relative to the important operational performance measures such as work center utilization, product flow times, and WIP inventory buildup at specific workstations, departments, or the entire factory. FactoryFLOW could be used to develop handful—say three—layouts that minimize material handling costs by trial and error and then test these layouts for their operational performance via Plant Simulation. Plant Simulation also has a genetic algorithm-based optimizer feature that can help develop near-optimal system parameters such as the number of machines and material handling devices of a given type to include in the layout.
COALPROM — A coal preparation plant simulation
Published in Y.J. Wang, R. Larry Grayson, Richard L. Sanford, Use of Computers in the Coal Industry, 2020
Eugene C. Hise, Vanston R. Brantley
Process modeling and plant simulation are routinely used in many industries as engineering design and plant operation aids. In the coal industry, many calculational procedures are so complex that, by the time the information is generated by conventional methods, it is only of historical interest. Partial analysis methods and other short cuts have been devised to approximate the complex processes of sizing and cleaning in order to produce results in a reasonable period of time. Today, the market value of clean coal, the cost of refuse disposal, and the capital and operating costs of plants make these approximate methods prohibitively expensive to the coal industry. Further; microcomputers are now available which possess the speed and capacity to perform the many calculations necessary to accurately model a coal preparation process.
Review of simulation software for cyber-physical production systems with intelligent distributed production control
Published in International Journal of Computer Integrated Manufacturing, 2023
N. Paape, J.A.W.M. Van Eekelen, M.A. Reniers
In both databases, the first 50 results were inspected. All mentions of simulation tools were collected, resulting in a list of 292 tools. The list of tools was then validated to examine whether any prominent tools were overlooked using this search strategy. The list was first compared with a list of tools based on the pre-knowledge of the authors of this paper and included the following simulation tools: Anylogic, Arena, Netlogo, Plant Simulation, Enterprise Dynamics, MASON, SimEvents, and SimPy. The list was then compared with a list of hybrid simulation tools mentioned in literature (Brailsford et al. (2019), Scheidegger et al. (2018), Pawlewski, Golinska, and Dossou (2012), and Pal et al. (2020)). This literature comparison list consists of Anylogic, ExtendSim, FlexSim, Simio, Simul8, Automod, MASON, and SimEvents. All tools in these two lists were encountered at least 3 times using this search strategy, with the most-encountered tool being Anylogic with 43 encounters.
Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors
Published in International Journal of Production Research, 2019
Kai Ding, Felix T.S. Chan, Xudong Zhang, Guanghui Zhou, Fuqiang Zhang
As the methods to build the Digital Twin of a part have been widely researched, this paper focusses on the Digital Twin modelling of shop floor. Modelling tools such as Plant Simulation®, Demo 3D® and others are available. Reference models with templates of static attributes, motion script, control scheme and communication interface (Zhang et al. 2017) are adopted to initialise a Digital Twin model of PSF, i.e. CSF. This model not only contains the physical layout and 3D geometry information but also contains the dynamic engineered information of each physical object. Some of this information is inherited from the physical object's inherent attributes and parameters, while some is dynamically synchronised from PSF. Afterwards, the ‘element-behaviour-rule’ multi-dimensional modelling of smart shop floor is established to simulate the real-time operating performance, such as process planning simulation, production scheduling simulation and exception/error simulation.
A routine-based framework implementing workload control to address recurring disturbances
Published in Production Planning & Control, 2018
Sayyed Shoaib-ul-Hasan, Marco Macchi, Alessandro Pozzetti, Ruth Carrasco-Gallego
For simulation purposes ‘Plant Simulation’ software is used (Bangsow 2016). The simulation model considers eight assembly cells where each cell is dedicated to a particular PF and has its own dedicated worker(s) trained to perform the operations on all the product models belonging to the dedicated PF. Table 5 provides the input data for the simulation.