Risk Analysis regarding the costs of a residential civil works project via Python

Detalhes bibliográficos
Autor(a) principal: Santos, José Antônio Lima
Data de Publicação: 2022
Outros Autores: Cardoso, Iágo Prado, Silva, Jaqueline Maria da, Brito, Alexandre Faissal
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/28203
Resumo: It is essential to analyze the projects risks that you want to execute, especially in the construction sector, cause they are highly regarded as external conditions such as: climatic, political and public health issues. Most designers use a magnification factor to define the maximum cost, however, it can be considered an overpassed way. To innovate the risk analysis in Civil Construction, the present work carried out two simulations via computational Monte Carlo Method in the Python Programming Language. The first simulation was made using the Risk Oriented Identification Approach Method and the Precedence Diagram Method and PERT/CPM Tool. Based on the above considerations, the main goal is to present a comparison between two risk analysis methodologies to later help civil construction entrepreneurs to better assess the budgetary risks of their projects. Through the results obtained by the computer simulation process were possible the identification of possible costs, and from then on, planning the best project planning.
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spelling Risk Analysis regarding the costs of a residential civil works project via PythonAnálisis de riesgos de los costes de un proyecto de obra civil residencial vía PythonAnálise de Risco dos custos de um projeto de obra civil residencial via PythonComputer SimulationMonte Carlo MethodPython LanguageAnalysisRiskProjects.Simulação ComputacionalMétodo de Monte CarloLinguagem PythonAnáliseRiscoProjetos.Simulación por ordenadorMétodo de Monte CarloLenguaje PythonAnálisisRiesgoProyectos.It is essential to analyze the projects risks that you want to execute, especially in the construction sector, cause they are highly regarded as external conditions such as: climatic, political and public health issues. Most designers use a magnification factor to define the maximum cost, however, it can be considered an overpassed way. To innovate the risk analysis in Civil Construction, the present work carried out two simulations via computational Monte Carlo Method in the Python Programming Language. The first simulation was made using the Risk Oriented Identification Approach Method and the Precedence Diagram Method and PERT/CPM Tool. Based on the above considerations, the main goal is to present a comparison between two risk analysis methodologies to later help civil construction entrepreneurs to better assess the budgetary risks of their projects. Through the results obtained by the computer simulation process were possible the identification of possible costs, and from then on, planning the best project planning.Es fundamental hoy en día analizar los riesgos de los proyectos que se quieren implementar, principalmente en el sector de la construcción civil, ya que es altamente vulnerable las condiciones externas como el clima, la política y la salud pública. La mayoría de los diseñadores utilizan un factor de escala para definir el gasto máximo, pero es una forma acarcaica. Con el fin de modernizar el análisis de riesgos en la construcción civil, el presente trabajo elaboró dos simulaciones computacionales a través del Método Monte Carlo implementado en el Lenguaje de Programación Python. La primera simulación se realizó utilizando el Método de Enfoque de Identificación Orientado al Riesgo y la segunda el Método de Diagrama de Precedencia y la Herramienta PERT / CPM. Dado lo anterior, el principal objetivo es ayudar a los emprendedores de la Construcción Civil a evaluar mejor los riesgos presupuestarios de sus proyectos. A través de los resultados obtenidos por la simulación por computadora, fue posible identificar los posibles costos máximos y, a partir de ahí, planificar para organizar mejor el progreso del proyecto.É fundamental nos dias atuais analisar os riscos dos projetos que se deseja implementar, principalmente no setor da construção civil, pois os mesmos são altamente vulneráveis a condições externas, como: questões climáticas, políticas e de saúde pública. A maioria dos projetistas usa um fator de majoração para definir o gasto máximo, porém, essa pode ser considerada uma forma ultrapassada. Para inovar a análise de risco na construção civil, o presente trabalho elaborou duas simulações computacionais via Método de Monte Carlo implementadas na Linguagem de Programação Python. A primeira simulação foi feita usando o Método de Abordagem de Identificação Orientada ao Risco e a segunda o Método de Diagrama de Precedência e Ferramenta PERT/CPM. Diante do exposto, o principal objetivo é apresentar uma comparação entre duas metodologias de análise de risco e, posteriormente, auxiliar empreendedores da construção civil a avaliarem melhor os riscos orçamentários de seus projetos. Através dos resultados obtidos pela simulação computacional foi possível identificar os possíveis custos máximos, e a partir de então planejar e organizar melhor o andamento do projeto.Research, Society and Development2022-04-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2820310.33448/rsd-v11i5.28203Research, Society and Development; Vol. 11 No. 5; e20411528203Research, Society and Development; Vol. 11 Núm. 5; e20411528203Research, Society and Development; v. 11 n. 5; e204115282032525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/28203/24478Copyright (c) 2022 José Antônio Lima Santos; Iágo Prado Cardoso; Jaqueline Maria da Silva; Alexandre Faissal Britohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSantos, José Antônio Lima Cardoso, Iágo Prado Silva, Jaqueline Maria da Brito, Alexandre Faissal 2022-04-17T18:18:56Zoai:ojs.pkp.sfu.ca:article/28203Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:45:41.467964Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Risk Analysis regarding the costs of a residential civil works project via Python
Análisis de riesgos de los costes de un proyecto de obra civil residencial vía Python
Análise de Risco dos custos de um projeto de obra civil residencial via Python
title Risk Analysis regarding the costs of a residential civil works project via Python
spellingShingle Risk Analysis regarding the costs of a residential civil works project via Python
Santos, José Antônio Lima
Computer Simulation
Monte Carlo Method
Python Language
Analysis
Risk
Projects.
Simulação Computacional
Método de Monte Carlo
Linguagem Python
Análise
Risco
Projetos.
Simulación por ordenador
Método de Monte Carlo
Lenguaje Python
Análisis
Riesgo
Proyectos.
title_short Risk Analysis regarding the costs of a residential civil works project via Python
title_full Risk Analysis regarding the costs of a residential civil works project via Python
title_fullStr Risk Analysis regarding the costs of a residential civil works project via Python
title_full_unstemmed Risk Analysis regarding the costs of a residential civil works project via Python
title_sort Risk Analysis regarding the costs of a residential civil works project via Python
author Santos, José Antônio Lima
author_facet Santos, José Antônio Lima
Cardoso, Iágo Prado
Silva, Jaqueline Maria da
Brito, Alexandre Faissal
author_role author
author2 Cardoso, Iágo Prado
Silva, Jaqueline Maria da
Brito, Alexandre Faissal
author2_role author
author
author
dc.contributor.author.fl_str_mv Santos, José Antônio Lima
Cardoso, Iágo Prado
Silva, Jaqueline Maria da
Brito, Alexandre Faissal
dc.subject.por.fl_str_mv Computer Simulation
Monte Carlo Method
Python Language
Analysis
Risk
Projects.
Simulação Computacional
Método de Monte Carlo
Linguagem Python
Análise
Risco
Projetos.
Simulación por ordenador
Método de Monte Carlo
Lenguaje Python
Análisis
Riesgo
Proyectos.
topic Computer Simulation
Monte Carlo Method
Python Language
Analysis
Risk
Projects.
Simulação Computacional
Método de Monte Carlo
Linguagem Python
Análise
Risco
Projetos.
Simulación por ordenador
Método de Monte Carlo
Lenguaje Python
Análisis
Riesgo
Proyectos.
description It is essential to analyze the projects risks that you want to execute, especially in the construction sector, cause they are highly regarded as external conditions such as: climatic, political and public health issues. Most designers use a magnification factor to define the maximum cost, however, it can be considered an overpassed way. To innovate the risk analysis in Civil Construction, the present work carried out two simulations via computational Monte Carlo Method in the Python Programming Language. The first simulation was made using the Risk Oriented Identification Approach Method and the Precedence Diagram Method and PERT/CPM Tool. Based on the above considerations, the main goal is to present a comparison between two risk analysis methodologies to later help civil construction entrepreneurs to better assess the budgetary risks of their projects. Through the results obtained by the computer simulation process were possible the identification of possible costs, and from then on, planning the best project planning.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-03
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/28203
10.33448/rsd-v11i5.28203
url https://rsdjournal.org/index.php/rsd/article/view/28203
identifier_str_mv 10.33448/rsd-v11i5.28203
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/28203/24478
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 11 No. 5; e20411528203
Research, Society and Development; Vol. 11 Núm. 5; e20411528203
Research, Society and Development; v. 11 n. 5; e20411528203
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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