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Autodesk LATAM

Desarrollo de modelos BIM para coordinación 3D y estimación de cantidades

Natalia Kramer
August 5, 2024

AUTORES:

Bach.Ing. Mauricio Briceño

Arq.Carolina Gasparri, Mgtr. BIM y Diseño Integrado, PMP®

Arq.Sebastian Sanabria, MBA, PMP®, DASM®

 

Estudio ESE es una consultora BIM, fundada en 2014. Es la única en Latinoamérica certificada con la ISO 9001. Su equipo, compuesto por más de 30 integrantes, tiene un variado portafolio que incluye 10 años de experiencia internacional en BIM en países como EE.UU., Canadá, México, España, Bahamas, Chile, Brasil, Paraguay, Perú, Ecuador y Uruguay. Ha colaborado en más de 300 proyectos, tanto públicos como privados, cubriendo más de 5.000.000 m² en BIM.

Entre los proyectos desarrollados por Estudio ESE destaca el edificio The Edge, ubicado en Carrasco, Montevideo, Uruguay. Este proyecto, diseñado por Foster & Partners y Ponce de León Arquitectos, está compuesto por 8 viviendas de lujo distribuidas en tres niveles y un subsuelo, con un área de 6.283 m². Estudio ESE participó en el modelado de disciplinas, coordinación del modelo y obtención de cuantificaciones utilizando la metodología BIM, gestión de calidad con BIM Collab y los softwares Revit 2021 y Navisworks Manage de Autodesk.

Para conseguir excelentes resultados en el trabajo, Estudio ESE utilizó procesos y protocolos estandarizados para las tareas de modelado, coordinación y cuantificaciones. De esta forma, los clientes pueden obtener información fiable a partir del entregable final para la toma de decisiones a lo largo de las etapas del ciclo de vida del proyecto.

DESAFÍOS:

A partir de documentación 2D, memorias y estándares alineados con la normativa vigente, se desarrolló el modelado BIM que permitiría al cliente, interesado clave del proyecto, consultar información precisa en el momento oportuno, realizar controles de costes de la obra y solucionar problemas constructivos de manera anticipada.

Destacamos los desafíos más importantes que encontramos:

  • Desarrollar un protocolo de modelado apto para este proyecto en particular.
  • Analizar la documentación proporcionada por el cliente para el desarrollo del modelo.
  • Crear listas de verificación para el modelado de disciplinas, obtención de cuantificaciones y detección de interferencias.
  • Establecer un formato de intercambio de información para comunicar las incidencias al cliente de forma efectiva.
  • Interpretar los sistemas complejos que componen la edificación.
  • Garantizar la trazabilidad de las incidencias al realizar los análisis de interferencias.
  • Categorizar y organizar el modelo para obtener cuantías acordes a las necesidades del cliente.
  • Identificar las entidades a través de estándares de nombrado para poder realizar consultas y organizar la información de manera clara.

PROCESO:

Desde el inicio, organizamos los paquetes de trabajo con herramientas de gestión de proyectos para asegurar altos estándares de calidad en nuestros modelos. Utilizamos Autodesk Construction Cloud como entorno común de datos, facilitando la colaboración y asegurando acceso a la información más actualizada para minimizar errores y mejorar la productividad.

Al planificar las etapas del proyecto, estructuramos los modelos, seleccionamos los recursos tecnológicos y humanos necesarios, y diseñamos estrategias específicas para el modelado de cada disciplina. Además, establecimos un procedimiento para generar reportes de interferencias basado en los mapas de procesos de nuestra organización.

Se crearon dos modelos en archivos independientes: uno contenía la disciplina de estructuras y el otro, las disciplinas de sanitaria, eléctrica, térmica y protección contra incendio. El modelo de arquitectura fue proporcionado por el cliente y se consolidó con los demás modelos a través de los vínculos de Revit siguiendo el esquema detallado.

Las cuatro disciplinas se integraron en un único modelo, utilizando la clasificación de sus sistemas para una división eficiente y organizada. Esto permitió crear vistas independientes para cada disciplina y vistas de coordinación para detectar posibles colisiones antes de las interferencias.

La estrategia de modelado implicó un proceso iterativo de modelado y revisión de calidad. Tras validar la calidad del modelo mediante listas de verificación, se registraron las incidencias con una herramienta que maneja archivos BCF (Building Collaboration Format), permitiendo un control preciso de las incidencias a medida que avanzaba el proyecto.

Esta plataforma también facilitó la revisión colaborativa de las incidencias dentro del entorno de Revit, utilizando diferentes parámetros para filtrar la información y mantener un control riguroso del modelado.

Para detectar interferencias, se exportaron los modelos en formato .nwc y se creó un archivo federado .nwf con todas las disciplinas en Autodesk Navisworks Manage. Esta herramienta proporciona gran versatilidad gracias a sus diversas funciones, incluyendo conjuntos de selección para agrupar elementos según necesidad. Además, utilizamos Clash Detective, una herramienta indispensable para realizar análisis detallados de interferencias.

Utilizando Navisworks, identificamos rápidamente las colisiones en el proyecto, organizándose según el estado de las incidencias. Después de agrupar y filtrar las colisiones, se generó un reporte en formato .html que proporciona información detallada sobre los elementos involucrados en las interferencias. Los datos del software incluyen la identidad, ubicación y otras propiedades relevantes de los elementos afectados.

Nuestra estrategia para abordar la detección de interferencias consistió en la división de cada nivel en sectores, desde el subsuelo a la superestructura, utilizando reglas y conjuntos de selección. Posteriormente, se agruparon las incidencias según su proximidad para reducir su número y delimitarlas con precisión. Este proceso se llevó a cabo de manera iterativa para asegurar la cobertura completa de todas las colisiones detectadas.

Después de recopilar la información, se elaboraron los reportes de interferencias como entregable final para el cliente. Estos reportes incluyen detalles relevantes de las interferencias para facilitar su rápida identificación, como las coordenadas de la grilla de referencia, el nivel del proyecto, el ID del elemento y el sector correspondiente. El flujo de trabajo utilizado para la detección de interferencias se describe detalladamente a continuación.

Para la asignación de prioridades de las interferencias, utilizamos un criterio basado en la flexibilidad del sistema y la dimensión física de la interferencia. Por ejemplo, si la flexibilidad es baja y la dimensión es alta, asignamos una prioridad alta a la incidencia.

Al finalizar el modelado y realizar la coordinación de las disciplinas, se realizaron los cómputos de las disciplinas de Arquitectura y MEP. La estrategia consistió en identificar las entidades a cuantificar según los requisitos del cliente y luego filtrar los elementos del modelo por categorías y tipos. Utilizamos la herramienta de tablas de planificación de Revit, configurando parámetros como familia, nivel y tipo, lo que permitió extraer cuantificaciones precisas y fiables de los elementos arquitectónicos y de los sistemas del edificio. Estos cómputos se exportaron en formato .csv para procesarlos con softwares de cálculo.

Para lograr un buen resultado en este paso final de la cuantificación, fue clave el proceso de calidad mencionado previamente. En esta etapa, se verificó que los estándares de nombrado y criterios de modelado definidos en base al uso establecido para el modelo fueran adecuados, permitiendo el cierre del proyecto con un proceso sencillo de reporte y exportado de la información.

RESULTADOS:

El proyecto The Edge ejemplifica el éxito del modelado de disciplinas con BIM. Los contenedores de información optimizaron el uso futuro de recursos en la construcción y permitieron identificar errores constructivos con suficiente antelación para corregir el diseño en fases tempranas.

Se completaron las entregas de tres reportes de interferencias que abarcaban todos los niveles analizados en dos rondas. De un total de 16.598 elementos modelados en todas las disciplinas, se obtuvieron 4.983 interferencias al ejecutar el análisis. De dichas interferencias, se agruparon y clasificaron en 112 incidencias según su prioridad. Al finalizar el proyecto, se resolvieron 69, mientras que 43, todas de prioridad baja, quedaron mapeadas para ser trabajadas durante el avance de la construcción o en colaboración con el cliente.

Por otro lado, al obtener las cuantías del modelo, los gestores del proyecto obtuvieron información precisa en el momento adecuado para tomar decisiones informadas sobre la elección de contratistas postulantes a la ejecución de obra, así como un mejor manejo económico del proyecto en sí mismo.

La metodología BIM, siguiendo con los lineamientos establecidos por las normas ISO 9001 e ISO 19650, fue fundamental y beneficiosa para trabajar en un ecosistema eficiente, esencial en proyectos de esta escala y complejidad.

 

 

 

Natalia Kramer

Natalia Kramer se recibió de Arquitecta en la Universidad de Buenos Aries y completó el posgrado de BIM “Nuevas técnica proyectuales” en la misma Universidad. Realizó el curso sobre “Lean Construction” en la Universidad Tecnológica Nacional. Actualmente se desempeña como Industry Territory Sales Executive en Autodesk, especializada en la industria AEC Design & BIM. Su interés por las nuevas tecnologías la llevo a capacitarse y ejercer su profesión abocándose al desarrollo de BIM y las nuevas tendencias digitales.

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We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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