MODELO INTEGRADO DE PLANEJAMENTO E CONTROLE DE PROJETOS COM IA, PYTHON E N8N: ESTUDO DE CASO EM ENGENHARIA FOTOVOLTAICA.
Gespeichert in:
| Titel: | MODELO INTEGRADO DE PLANEJAMENTO E CONTROLE DE PROJETOS COM IA, PYTHON E N8N: ESTUDO DE CASO EM ENGENHARIA FOTOVOLTAICA. (Portuguese) |
|---|---|
| Alternate Title: | INTEGRATED MODEL FOR PROJECT PLANNING AND CONTROL USING IA, PYTHON AND N8N: A CASE STUDY IN PHOTOVOLTAIC ENGINEERING. (English) MODELO INTEGRADO DE PLANIFICACIÓN Y CONTROL DE PROYECTOS COM IA, PYTHON Y N8N: ESTUDIO DE CASO EM INGENIERÍA FOTOVOLTAICA. (Spanish) |
| Autoren: | Bruno Pedrosa, Carlos, Vilela Sales, Lailson, Roberto Sartin, Karla |
| Quelle: | Revista Foco (Interdisciplinary Studies Journal); 2025, Vol. 18 Issue 11, p1-27, 27p |
| Schlagwörter: | ARTIFICIAL intelligence, PROCESS optimization, PYTHON programming language, SUPERVISION, PHOTOVOLTAIC power generation, WORKFLOW management systems, AGILE software development, PROJECT management |
| Abstract (English): | This article proposes the optimization of processes through the integration of N8N software with Artificial Intelligence (AI), aiming at efficiency, standardization, and reliability in management. OpenAI technology was used as the analytical basis. The case study involved the planning and execution of a photovoltaic solar power plant, applying AI to identify opportunities for improvement and standardization in construction stages. The analysis, based on the Work Breakdown Structure (WBS) from MS Project, allowed for the refinement of the sequence of activities and their interdependencies. After updating the WBS, a Python system was developed to organize data and generate monitoring reports, highlighting delayed, ongoing, and planned activities. Automation provided an integrated view of physical performance and schedule adherence, increasing monitoring accuracy. A checklist based on agile methodologies was implemented to standardize information and support executive activities. AI was applied in predictive analyses considering planned start and end dates, estimated duration, and daily progress, enabling the detection of delays and the development of corrective action plans, strengthening the integration between planning and execution. The results show that the combination of AI, N8N, and Python can be applied to well-structured organizational workflows, extending beyond electrical engineering. The solution identified critical points, proposed corrections, and detected interferences affecting productivity and deadlines. It is concluded that process analysis based on real data, integrated with AI and automation, enhances operational performance, increases result predictability, and consolidates a management model oriented toward efficiency and technological innovation. [ABSTRACT FROM AUTHOR] |
| Abstract (Spanish): | Este artículo propone la optimización de procesos mediante la integración del software N8N con Inteligencia Artificial (IA), con el objetivo de lograr eficiencia, estandarización y confiabilidad en la gestión. Se utilizó la tecnología OpenAI como base analítica. El estudio de caso incluyó la planificación y ejecución de una planta solar fotovoltaica, aplicando IA para identificar oportunidades de mejora y estandarización en las etapas constructivas. El análisis, basado en la Estructura Desglosada del Proyecto (EDP) del MS Project, permitió mejorar la secuencia de actividades y sus interdependencias. Tras actualizar la EDP, se desarrolló un sistema en Python para organizar datos y generar informes de seguimiento, destacando actividades retrasadas, en curso y planificadas. La automatización proporcionó una visión integrada del desempeño físico y del cumplimiento de plazos, aumentando la precisión del monitoreo. Se implementó un checklist basado en metodologías ágiles para estandarizar la información y apoyar las actividades ejecutivas. La IA se aplicó en análisis predictivos considerando fechas de inicio y fin planificadas, duración estimada y avance diario, permitiendo detectar retrasos y elaborar planes de acción correctiva, fortaleciendo la integración entre planificación y ejecución. Los resultados muestran que la combinación de IA, N8N y Python puede aplicarse a flujos organizacionales bien estructurados, más allá de la ingeniería eléctrica. La solución identificó puntos críticos, propuso correcciones y detectó interferencias que afectan la productividad y los plazos. Se concluye que el análisis de procesos basado en datos reales, integrado con IA y automatización, potencia el desempeño operativo, aumenta la predictibilidad de resultados y consolida un modelo de gestión orientado a la eficiencia y la innovación tecnológica. [ABSTRACT FROM AUTHOR] |
| Abstract (Portuguese): | Este artigo propõe a otimização de processos por meio da integração do software N8N com Inteligência Artificial (IA), visando eficiência, padronização e confiabilidade na gestão. A tecnologia OpenAI foi utilizada como base analítica. O estudo de caso envolveu o planejamento e execução de uma usina solar fotovoltaica, aplicando IA para identificar oportunidades de melhoria e padronização nas etapas construtivas. A análise, baseada na Estrutura Analítica de Projeto (EAP) do MS Project, permitiu aprimorar a sequência das atividades e suas interdependências. Após atualizar a EAP, desenvolveu-se em Python um sistema para organizar dados e gerar relatórios de acompanhamento, evidenciando atividades em atraso, em andamento e previstas. A automação proporcionou visão integrada do desempenho físico e do cumprimento de prazos, aumentando a precisão no monitoramento. Um checklist baseado em metodologias ágeis foi implementado para padronização de informações e suporte às atividades executivas. A IA foi aplicada em análises preditivas considerando início e término planejados, duração estimada e avanço diário, permitindo detectar atrasos e elaborar planos de ação corretiva, fortalecendo a integração entre planejamento e execução. Os resultados mostram que a combinação de IA, N8N e Python pode ser aplicada a fluxos organizacionais bem estruturados, extrapolando a engenharia elétrica. A solução identificou pontos críticos, propôs correções e detectou interferências que impactam produtividade e prazos. Conclui-se que a análise de processos baseada em dados reais, integrada à IA e automação, potencializa a performance operacional, amplia a previsibilidade de resultados e consolida um modelo de gestão orientado por eficiência e inovação tecnológica. [ABSTRACT FROM AUTHOR] |
| Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Datenbank: | Complementary Index |
Full Text Finder 
Nájsť tento článok vo Web of Science | Abstract: | This article proposes the optimization of processes through the integration of N8N software with Artificial Intelligence (AI), aiming at efficiency, standardization, and reliability in management. OpenAI technology was used as the analytical basis. The case study involved the planning and execution of a photovoltaic solar power plant, applying AI to identify opportunities for improvement and standardization in construction stages. The analysis, based on the Work Breakdown Structure (WBS) from MS Project, allowed for the refinement of the sequence of activities and their interdependencies. After updating the WBS, a Python system was developed to organize data and generate monitoring reports, highlighting delayed, ongoing, and planned activities. Automation provided an integrated view of physical performance and schedule adherence, increasing monitoring accuracy. A checklist based on agile methodologies was implemented to standardize information and support executive activities. AI was applied in predictive analyses considering planned start and end dates, estimated duration, and daily progress, enabling the detection of delays and the development of corrective action plans, strengthening the integration between planning and execution. The results show that the combination of AI, N8N, and Python can be applied to well-structured organizational workflows, extending beyond electrical engineering. The solution identified critical points, proposed corrections, and detected interferences affecting productivity and deadlines. It is concluded that process analysis based on real data, integrated with AI and automation, enhances operational performance, increases result predictability, and consolidates a management model oriented toward efficiency and technological innovation. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 1981223X |
| DOI: | 10.54751/revistafoco.v18n11-135 |