| Dataflow | Generate Wall Surface Objects |
| Purpose | Calculate painting and plastering needed – per room or grouped by wall type. |
| Useful for | Site engineers, site managers, procurement teams, logistics planners, cost estimators. |
| Wrangling Type | “Enrich”. The Dataflow generates virtual Wall surface objects, where the data for painting and plastering will be related. |
| Use Cases | Estimating, planning, scheduling, procuring, and tendering of interior works. |
| Output | Wall surface objects with rich data, organized for efficient use. |
NOTE: This article relates closely to the next two articles in the Simplebim Dataflows series. Make sure to check the 002 - Generate Wall Surface Objects - for Waterproofing and Tiling, and the 003 - Add Location Information Using Nearby Spaces, right after this one!
Why It Matters
If you’ve worked with raw BIM models for planning, scheduling, or estimating interior works, you’ve likely run into a familiar issue: the data isn’t complete for your purpose. There is no clear object that identifies the right wall surfaces, which you are targeting for painting or plastering, not to mention, the related quantities.
But this is exactly the data you need for procurement, tendering, and site coordination.
Without Simplebim: slow, error-prone, not scalable
- Traditionally, for example, the painting area quantities have been calculated manually from 2D drawings. It is also possible to extract some data from the model using space perimeters and formulas that subtract openings – but it’s hard to repeat, easy to get wrong, and difficult to check.
- And there is another real limit, in terms of scalability: These methods don’t produce any actual model objects, so they cannot be visualized, grouped, or used, for example, in 4D simulations.
In short, it is data, but it is too labor-intensive to produce and unsuitable for use in a scalable way.
The Smart Way: with Simplebim Dataflows
In Simplebim, you can build your custom dataflow from a sequence of data processing steps. Or you can use ready-made dataflows wrapped in an easy-to-use configuration UI for your convenience.
Let’s now take your BIM data seriously, and see how you can get the job done with Simplebim: quickly, reliably, and automatically.
If you have Simplebim open, let’s explore dataflow and results along:
- Select the dataflow & Configure the parameters
- Run the dataflow
- Check & Use the results
1. Select the Dataflow
In the Dataflow Palette, click Add Step, select the dataflow you need, and Add it: for today’s use case, we need “Generate Wall Surfaces”.
Settings
Wall Surface Objects are generated from the common surface areas between Room Objects (Spaces) and their bounding Walls Objects. That’s why, under Parameters, we need to define these two sets of objects.
Which Properties will the generated Wall Surface Objects contain? We want to include the relevant properties from the related rooms and bounding walls. This makes organizing and using the surface data easy – for example, when preparing a Bill of Quantities.
Room Objects
Defines the rooms we are targeting. For waterproofing and tiling, these can be for example bedrooms and offices.
Wall Objects
Defines all relevant bounding walls of the previous Room Objects. Although you could put here all the walls of the model, ideally you would select only the relevant walls, for example, based on their construction type identifier.
Related Space
Defines the Property of the Room Objects, whose value will be copied to the generated Wall Surface Object; for example, the Space Name.
Related Element
Defines the Property of the Wall objects, whose value will be copied to the generated Wall Surface Object; for example, Building Element Construction Type.
This will help a lot later in organizing the data – for example in a Bill of Quantities.
Surface Color
Defines the color for the generated Surface Objects. This will help you visualize the results later – especially if you generate different types of Surface Objects in your model.
Clip Surface Objects to Specific Height
Defines a specific height for the generated Surface Object, from the room’s floor. If left empty, the generated Surface Object will have the full height of the overlapping area between the space and the bounding element. In our example we want the surfaces to cover the whole space surface, so we turn this off.
2. Run the Dataflow
When your setup is ready, just click Run Dataflow and let the software do what it is made for: delivering the results.
3. Check & Use the Results
Now you are ready to check and use the results: in fact, your model now contains:
- visible wall surface objects with their own geometry for waterproofing and tiling
- colorized according to your preference
- placed in the correct place in the model tree
- assigned to groups for easy access
- with identification data from rooms and walls
- and their correct quantities.
This data can now be organized, visualized, and reported in a scalable way.
How you can use the results:
- Group and report the generated data:
- by painting and plastering;
- by rooms (e.g. bedrooms and offices)
- by underlying wall construction (e.g. drywall vs. concrete)
- Use the surface objects in 3D visualizations to show to your customers:
- for example the work status, or the subcontractors;
- based on location (per room or apartment).
- Export the results to IFC and use the enriched data in any IFC-supporting application downstream.
- Export the results to Excel or data tables and use the data in any data visualization solution like PowerBI.
Up Next
Check out the next two articles in the series: they continue were we left off here.
In 002 - Generate Wall Surface Objects – for Waterproofing and Tiling, you will learn how to clip the wall surface to specific height, and apply the dataflow to waterproofing and tiling use cases.
Finally to learn how to organize the wall surfaces based on apartments in 003 - Add Location Information to Objects Using Nearby Spaces.
That’s the Power of Simplebim®: Automated BIM Data Processing
This is one high-impact use case of how you can turn raw BIM models and data into usable and scalable information.
Is it valuable for your work? We look forward to your comments, thank you!
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