Risk Prediction of Delay in the Execution of Public Works Through Fuzzy Logic

Case Study in the City of Manaus

Authors

DOI:

https://doi.org/10.31686/ijier.vol9.iss11.3471

Keywords:

Publics Works, Delay of Works, Causes of Delay, Fuzzy Logic

Abstract

In Manaus, delays in public constructions are not uncommon as their execution deadlines are often extrapolated, even though such deadlines are obtained through preliminary technical studies. The causes that give rise to such delays are varied ranging from the occurrence of rain to the addition of quantities of existing services or additions of new services. In this research, we sought to obtain a model, using fuzzy logic, to predict the risk of delay that some variables may cause in the period of execution of the work, allowing the public administration or the contracted company to adopt measures they consider essential to mitigate this delay. Initially, documentary and bibliographic research were carried out to identify the causes that most contribute to the occurrence of delays in the works. Once these causes were identified, the construction of the fuzzy inference system was started, with six of the most significant causes identified in the research being considered as linguistic variables, namely: the hiring factor, which corresponds to the quotient between the value of the proposal. of the company and the amount budgeted by the administration; the value of the work, which is the value of the contract for the work; the engineering execution drawing, which are the engineering drawings used in the works; the alteration of quantities, which are changes in the quantities of existing services or addition of new services; authorization from public agencies, which corresponds to the permission or support of any public agency or public company for the execution of the work; and the rain. For the simulation of the created fuzzy inference system, real data from four public works were entered, and the answers of this simulation were satisfactory because they are confirmed by the documentation of the respective works. It is concluded that the system proved to be useful, as it was possible to predict the risk of delay in the execution of public works in the city of Manaus, and it can be used by both the public administration and the contractor to mitigate the causes of delays in the execution of public works.

Downloads

Download data is not yet available.

References

ARAGÃO FILHO, S. A. P. “O custo do atraso em obras públicas viárias”, 2014, Disponível em <https://www.docsity.com/pt/o-custo-do-atraso-em-obras-publicas-viarias/4883562/> Acesso em 3 de agosto de 2020, 18h25min.

ARESE, M. C. “Maturidade da gestão de ativos físicos de processos: uma perspectiva sustentável utilizando lógica nebulosa", 2018, 228f, Tese (Doutorado em sistemas de gestão sustentáveis) – Universidade Federal Fluminense, Niterói, 2018.

ASSAF, S. A., AL-HEJJI, S. “Causes of delay in large construction projects”, International Journal of Project Management, v. 24, n. 4, pp. 349-357, 2006. DOI: https://doi.org/10.1016/j.ijproman.2005.11.010

BHATT, R., MACWAN, J. E. M. “Fuzzy Logic and analytic hierarchy process–based conceptual model for sustainable commercial building assessment for india”, Journal of Architectural and Engineering, v. 22, n. 1, pp. 04015009 (1-10), 2016. DOI: https://doi.org/10.1061/(ASCE)AE.1943-5568.0000184

BRASIL. Tribunal de Contas da União. Obras públicas: recomendações básicas para contratação e fiscalização de obras públicas, 2ª ed., Brasília: TCU, SECOB, 2009.

BRASIL. Lei nº 8.666/1993: licitações e contratos. Brasília: Senado Federal, Coordenação de Edições Técnicas, 2017.

Câmara Brasileira da Indústria da Construção. “Impacto econômico e social da paralisação das obras públicas”, 2018, Disponível em: <https://cbic.org.br/wp-content/uploads/2018/06/Impacto_Economico_das_Obras_Paralisadas.pdf> Acesso em 6 de agosto de 2020, 22h15min.

CHEN, G., PHAM, T. T. Introduction to fuzzy sets, fuzzy logic, and fuzzy control systems, Florida, CRC Press, 2019.

COLPO, I. et al. “Atrasos na execução das obras públicas: estudo em uma instituição federal de ensino superior”, Revista Produção Online, v. 18, n. 4, pp. 1322-1343, 2018. DOI: https://doi.org/10.14488/1676-1901.v18i4.2941

COUTO, J. P. P. M. “Incumprimento dos prazos na construção”, 2007, 491f, Tese (Doutoramento em Engenharia Civil – Processos de Construção) – Universidade do Minho. Portugal, 2007.

GAVIÃO, L. O., LIMA, G. B. A. “Indicadores de sustentabilidade para a educação básica por modelagem fuzzy”, Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental, v. 19, n. 3, pp. 274-297, 2015.

GUPTA, C., KUMAR, C. “Study of factors causing cost and time overrun in construction projects”, International Journal of Engineering Research & Technology, v. 9, n. 10, pp. 202-206, 2020.

HORTENGAL, M. V. “Aplicação da lógica fuzzy no controle do desempenho de estacas hélice continua”, 2016, 157f, Tese (Doutorado em geotecnica) – Universidade de Brasília. Brasília, 2016.

INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA. “Pesquisa anual da indústria da construção 2018”, 2020. Disponível em: <https://biblioteca.ibge.gov.br/visualizacao/periodicos/54/paic_2018_v28_informativo.pdf>. Acesso em 30 de maio 2021, 9h30min

LIMA, S. “Implementação de estratégias de controle utilizando lógica fuzzy e técnicas de controle vetorial em um software de elementos finitos”, 2016, 221f, Tese (Doutorado em Engenharia Elétrica) – Universidade Federal de Santa Catarina. Santa Catarina, 2016.

LIMMER, C. V. Planejamento, orçamentação e controle de projetos e obras, Rio de Janeiro: LTC – Livros Técnicos e Científicos, 1997.

MATTOS, A.D. Planejamento e controle de obras, 2 ed, São Paulo: Oficina de Textos, 2019.

REZENDE, S. O. (Org.). Sistemas inteligentes: fundamentos e aplicações, São Paulo: Manole, 2005.

ROSS, T. J. Fuzzy logic with engineering applications, 4 th, United Kingdom, John Wiley & Sons, 2017.

SIMÕES, M. G., I. S. SHAW. Controle e modelagem fuzzy, 2 ed. rev. e ampl, São Paulo: Edgard Blucher: FAPESP, 2007.

VIEIRA, A. S. A. “Avaliação a suscetibilidade de deslizamento de terra na bacia hidrográfica rio trombetas via lógica fuzzy”, 2018, 93f, Dissertação (Mestrado em Engenharia Civil) – Instituto de Tecnologia da Universidade Federal do Pará. Pará, 2018.

ZIDANE, Y. J-T., ANDERSEN, B. “The top 10 universal delay factors in construction projects”, International Journal of Managing Projects in Business, v. 11, n. 3, pp. 650-672, 2018. DOI: https://doi.org/10.1108/IJMPB-05-2017-0052

Downloads

Published

01-11-2021

How to Cite

Valente, A., & Nascimento, M. (2021). Risk Prediction of Delay in the Execution of Public Works Through Fuzzy Logic: Case Study in the City of Manaus. International Journal for Innovation Education and Research, 9(11), 317–337. https://doi.org/10.31686/ijier.vol9.iss11.3471