Barrio 31: Team Collaboration in Revit

Recap: This post is our 2nd installation of our series of blog posts covering the Barrio 31 Project. Villa 31, one of the largest poverty stricken neighborhoods in Argentina is undergoing a massive renewal into an official city neighborhood: "Barrio 31". Key project challenges include a lack of as-built documentation; the scope and size of measurements needed; short project timeline; and need for quality and consistency of data during hand-off. Our post today covers the development of custom applications to reduce manual effort in measurement & design.

Consistency is Key

Consistency in such a large project is crucial. Converting X amount of point cloud into a BIM model in this time frame could only happen through the collaboration of a large synchronized team. A growing team of people populate models and drawings concurrently, creating a great number of versions and alternatives. A BIM workflow was a clear necessity. With over 6500 structures to survey, measure, and model, even a marginal workflow improvement could lead to massive time savings. We saw this project as a good opportunity to put our abilities to the test on creating a platform that could:

  • Increase the reach of our data set:

    • Ensuring that more people get information directly from a reliable source of truth.

  • Make data more usable to our stakeholders:

    • Automate deliverables, reports, and data transformations to reliably narrow data to what the individual cares about.

  • Expand our capabilities of data expression:

    • Our growing library of techniques for working with BIM data allows us to tackle ever larger challenges.

The Voyansi Team began the project by documenting the existing 10-step workflow to understand potential bottlenecks in the process. This 100% manual workflow could take up to 24 hours per structure. We identified Steps 5-9 as areas for possible automation:

  1. Create Masses in Revit from Point Clouds.

  2. Create Model for a determined zone using the appropriate Revit template.

  3. Link the mass created.

  4. Start modeling the Existing phase crossing data from the Point Cloud, Google Maps, and photos of the site, using the Mass as base.

  5. Apply Design changes on a second Revit phase (Enhancement).

  6. Create documentation for both phases (Existing and Enhancement).

  7. Tag and annotate the sheet set for each parcel.

  8. Perform a quantity take-off using Revit schedules.

  9. Export documentation and quantity take-off

  10. Deliver.

Automation Approach

Voyansi developed a number of Revit tools using Python, Dynamo, and pyRevit that were installed on every workstation. These new tools allowed the user to control the following steps of the workflow previously described:

  1. Step 5: The Government's design intent in the shape of BIM elements was transferred to the model through a set of tools for this purpose, written in Python and executed through pyRevit.

  2. Steps 6-7: Drawings were created for existing conditions and proposed design. The drawings featured a title block where information was automatically populated (parcel, lot, sector, etc). Drawings featured different views (front, rear, lateral, etc) and included a keymap.

  3. Steps 8-9: Starting with an Excel template spreadsheet, Dynamo scripts were ran using each parcel's number. This spreadsheet was automatically filled in a precise way in a matter of seconds. This was done once per parcel as each one had its own QTO spreadsheet.

The Outcome

  • Over 100k man hours saved during the measurement and documentation process.

  • Improved consistency measurement data in the system.

  • Quality Assurance throughout the whole process.

  • Reduced time dedicated to Quality Control.

  • Reduced time on less important repetitive work to afford the team time to focus on more important design-oriented tasks.

  • Improved documentation delivery time so work on site would start without delays.

  • Consistency was gained among the team drawings (35 people were submitting CDs simultaneously).

  • Design and criteria improved as the architects were able to focus on the designs instead of repetitive tasks.

  • For large volume projects were repetitive tasks are identified, Revit automation reduced the amount of time required from each team member, cut costs and improved the quality of the deliverables significantly (in this case 300%).

  • Identified use cases and the feasibility of an integrated platform to showcase models, their data, and make that accessible and interactive through nothing more than a web browser (even from mobile).