Automação e otimização da estimativa de custos na construção civil: uma revisão sistemática de tecnologias digitais emergentes
DOI:
https://doi.org/10.46421/sibragec.v14i.7814Palabras clave:
Automação da estimativa de custos, inteligência artificial na construção, Building Information Modeling (BIM), machine learningResumen
Os métodos tradicionais de orçamentação estão sujeitos a imprecisões devido à falta de integração entre as fases do projeto. A aplicação do Building Information Modeling (BIM), apesar de difundido na construção civil, ainda enfrenta desafios relacionados à orçamentação, como baixa interoperabilidade entre softwares e ausência de padronização. Contudo, abordagens como inteligência artificial, machine learning e redes neurais vêm sendo empregadas na previsão de custos na construção, ampliando a capacidade analítica e a precisão das estimativas. Este trabalho propõe uma revisão sistemática da literatura para identificar como a associação dessas tecnologias pode auxiliar na otimização e automação na estimativa de custos na construção civil. A metodologia incluiu a análise de 160 artigos publicados entre 1998 e 2025, que abordaram o uso dessas tecnologias na elaboração de orçamentos e gestão de custos. Os resultados indicaram tendências emergentes, como o uso de modelos híbridos que combinam redes neurais com algoritmos de otimização (como AOA e PSO) e a integração entre BIM e sistemas de deep learning para previsão de custos. Este estudo contribui ao sistematizar o estado da arte e apoiar profissionais na adoção de soluções mais precisas, automatizadas e orientadas por dados para orçamento e controle de custos na construção civil.
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Derechos de autor 2025 SIMPÓSIO BRASILEIRO DE GESTÃO E ECONOMIA DA CONSTRUÇÃO
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