Identification of the main methods used in simulation projects

Montevechi, José Arnaldo Barra; Pereira, Tábata Fernandes; Silva, Carlos E. S. da; Miranda, Rafael de Carvalho; Scheidegger, Anna Paula Galvão

doi:10.1109/wsc.2015.7408507

Cited by 18 publications

(8 citation statements)

References 14 publications

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“…A simulação de eventos discretos é uma ferramenta de apoio à tomada de decisão que vem sendo cada vez mais utilizada para estudar sistemas complexos. Vários métodos de simulação são encontrados na literatura e cada um possui suas peculiaridades para guiar os analistas durante o desenvolvimento de projetos (MONTEVECHI et al, 2016). Segundo Law (2014) a DES tem como característica descrever mudanças de estado de um sistema, em intervalos discretos de tempo, a partir da ocorrência de eventos, geralmente de natureza estocástica.…”

Section: Simulação a Eventos Discretosunclassified

Análise De Frameworks Que Integram as Metodologias Lean Six Sigma E Simulação a Eventos Discretos: Uma Revisão Sistemática De Literatura

LÚCIO

Miranda

2022

Anais Do Encontro Nacional De Engenharia De Produção

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Section: Simulação a Eventos Discretosunclassified

Análise De Frameworks Que Integram as Metodologias Lean Six Sigma E Simulação a Eventos Discretos: Uma Revisão Sistemática De Literatura

LÚCIO

Miranda

2022

Anais Do Encontro Nacional De Engenharia De Produção

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“…Figure 1 shows the conventional simulation modelling process per Robinson [6]. The most critical steps of simulation modelling are conceptual modelling, detailed model creation, and experiment conduction [35]. The simulation modelling process is generally undertaken by the analyst with partial industry client participation.…”

Section: Conceptual Modelling Approachesmentioning

confidence: 99%

“…In the context of simulation, validation refers to the process of confirming that the behaviour of the model is a sufficiently accurate representation of the real operations system [12]. Validation should ideally be involved in each life cycle of model development [63,79] because it decides the authenticity of the simulation model compared with the practical system [35]. However, model validation is a challenge for many simulation projects, as there may be limited opportunities to apply it.…”

Section: §4 Interactive Face Validationmentioning

confidence: 99%

Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics

et al. 2022

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Background: Logistics problems involve a large number of complexities, which makes the development of models challenging. While computer simulation models are developed for addressing complexities, it is essential to ensure that the necessary operational behaviours are captured, and that the architecture of the model is suitable to represent them. The early stage of simulation modelling, known as conceptual modelling (CM), is thus dependent on successfully extracting tacit operational knowledge and avoiding misunderstanding between the client (customer of the model) and simulation analyst. Objective: This paper developed a methodology for managing the knowledge-acquisition process needed to create a sufficient simulation model at the early or the CM stage to ensure the correctness of operation representation. Methods: A minimum viable model (MVM) methodology was proposed with five principles relevant to CM: iterative development, embedded communication, soliciting tacit knowledge, interactive face validity, and a sufficient model. The method was validated by a case study of freight operations, and the results were encouraging. Conclusions: The MVM method improved the architecture of the simulation model through eliciting tacit knowledge and clearing up communication misunderstandings. It also helped shape the architecture of the model towards the features most appreciated by the client, and features not needed in the model. Originality: The novel contribution of this work is the presentation of a method for eliciting tacit information from industrial clients, and building a minimally sufficient simulation model at the early modelling stage. The framework is demonstrated for logistics operations, though the principles may benefit simulation practitioners more generally.

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“…[5][6][7] There are several simulation research methods presented in the literature, each one with its own characteristics, strengths, and instructions with which to assist analysts during project development. 8 These methods are important to guide the analysts over a project's execution by listing the logical sequence of steps to be followed in that case. 9 Most simulation projects may be divided into three steps: conception, implementation, and analysis.…”

Section: Introductionmentioning

confidence: 99%

Application of a management and storage system for knowledge generated from simulation projects as a teaching and assessment tool

et al. 2021

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During the development of a simulation project, people involved in the study acquire greater knowledge of the system being simulated. However, this knowledge is usually not externalized and ends up being lost at the end of the project. In this context, knowledge management allied with information technology may assist in information management and enable the collection, storage, and dissemination of knowledge. Thus, this paper aims to discuss and present a knowledge management system to manage and to store the knowledge generated by analysts in simulation projects. Our intention was to demonstrate a way that the knowledge can be stored and accessed at any moment by anyone to recover the development process and avoid mistakes during a simulation project. In order to achieve this goal, some graduate and undergraduate simulation courses at a Brazilian federal university were used as objects of study. At the end of the study, it was concluded that knowledge management integrated with information technology contributes to the work of simulation analysts by supporting information and knowledge management throughout the stages of the simulation projects.

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Identification of the main methods used in simulation projects

Cited by 18 publications

References 14 publications

Análise De Frameworks Que Integram as Metodologias Lean Six Sigma E Simulação a Eventos Discretos: Uma Revisão Sistemática De Literatura

Análise De Frameworks Que Integram as Metodologias Lean Six Sigma E Simulação a Eventos Discretos: Uma Revisão Sistemática De Literatura

Minimum Viable Model (MVM) Methodology for Integration of Agile Methods into Operational Simulation of Logistics

Application of a management and storage system for knowledge generated from simulation projects as a teaching and assessment tool

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