The Reality Capture Journey - Part 4

Welcome to the final chapter of The Reality Capture Journey! I deeply appreciate you sticking with me as I’ve shared the details behind this challenging story. If you've followed along from the beginning, you've already learned how we estimated, laser scanned, and 3D modeled this enormous Central Utility Plant building.

Let’s put things into perspective one last time: more than five weeks of scanning and over 6,500 hours of 3D modeling spread across eight months. The result? Twenty-five Revit models—a digital beast with hundreds of pieces of equipment and systems shaping the digital replica of this facility.

In this article, I’ll walk you through our BIM for facility management workflow, with a focus on how we collected and structured essential data for building operations. Buckle up and enjoy the last stretch!

BIM for FM—What's that all about?

Before jumping into the specifics, let’s untangle what BIM for FM truly means. BIM provides the foundation for creating a live digital replica of an existing facility, widely known as Digital Twin. The purpose? To mirror real-time operational data to optimize building performance and predict future maintenance needs. BIM's 3D visualization capabilities empower facility managers to better understand and analyze building systems, enhancing troubleshooting and communication with operators and other stakeholders.

A true as-built 3D model is pure gold for owners and facility managers, as BIM models can also be leveraged for:

• Space and Occupancy Management: Ensuring optimal space utilization.
• Maintenance Planning and Execution: Enabling proactive and preventive maintenance by integrating operation manuals and other information to reduce downtime.
• Energy and Sustainability Management: Monitoring energy consumption and enhancing building performance.
• Control Operations: Leveraging the Internet of Things (IoT) and Building Management Systems (BMS), for effective resource allocation.
• Interoperability and Collaboration: Utilizing open data standards (like COBie and IFC) to ensure BIM models are compatible with various facility management software, fostering seamless collaboration across teams.
• Lifecycle Management: Maintaining relevant and accessible data from construction through operation.

Now that we’ve covered the basics, let’s dig deeper into our data collection process. For a project of this magnitude, our approach needed to address several key questions:

• What data would we integrate into the BIM models?
• Given the density and complexity of this facility, how could we ensure scalability and efficiency?
• What tools would be best suited to help non-BIM/3D users gather this essential information?

In other words, how could we ensure that both the modeling team and the site crew (our client, the engineering company) capture critical data efficiently while maintaining smooth communication? Let’s unpack the details and review the workflow.

Our Data Collection Workflow

Once the 3D modeling was completed, our team shifted focus from geometry to metadata. As part of our scope, we committed to gathering specific information on all building assets, including mechanical, plumbing, and electrical equipment, along with their associated systems. Essentially, this process involved collecting, centralizing, and structuring the as-built data before integrating it into the Revit models. The inventory process followed two main strategies:

• Systems data capture: We extracted system names from ductwork and piping labels visible in the point cloud data and panoramic views.
• Assets data capture: we retrieved the information from equipment tags.

Needless to say, labeling the assets and systems of this highly congested facility demanded significant effort. As anticipated, capturing 100% of the information solely from the scan data proved nearly impossible. To handle this large-scale challenge effectively, our collection and tagging process involved multiple iterations, with assets and systems addressed separately.

Systems Data Collection Process

Here’s an overview of our workflow for identifying the system names within this extensive pipe and ductwork network:

Step 1 - 360 Panoramic Views: Once the pipe and ductwork lines were populated in Revit along with their corresponding fittings and accessories, the team conducted a detailed revision of the 360 panoramic views for systems assignment. This first pass involved switching between the views taken by the scanners and labeling the systems directly in the models.

*To streamline the process, we asked the client to provide the system names for each area, so we could align the names available in the labels with the actual systems known by the facility team. For example: labels such as ‘Backwash’, ‘Soft Water Inlet’, and ‘Treated Water’ were unified in the models in a single system called ‘Soft Water’.

Step 2 - 2D Markups: After the initial pass was completed, we documented each area in 2D floor plans to assist the site team in gathering the missing system names for pipes and ductwork. To flag the missing data, we utilized a system called ‘Unconfirmed’, shown in light blue on all drawings. These sheets were then uploaded to the client’s Autodesk BIM360 hub, allowing the site crew to access them on their iPads and capture the majority of the systems at once.

*At this stage, 2D floor plans were preferred over 3D tools to capture most of the data, as site crews are sometimes less familiar with navigating a 3D environment.

Step 3 - 3D Markups: Once the information from the 2D markups was incorporated into our Revit models, we used Newforma to track in 3D any remaining unconfirmed systems. Newforma is a software designed to enhance communication and collaboration among project stakeholders by providing a centralized platform for issue tracking and resolution (thanks, ChatGPT!). With this tool, we assisted our client in pinpointing the remaining lines, particularly improving visibility in complex areas where multiple lines were closely grouped or stacked.

Assets Data Collection Process

For asset data collection, we developed a slightly different methodology. To make our approach straightforward and user-friendly, we used 2D floor plans combined with schedules, allowing the site crew to provide the required data efficiently. In addition to improving communication between the office and site teams, this approach made it easier to identify and number assets while also providing space in the drawings for the client’s input. Our workflow essentially followed these steps:

Step 1 - Shared Parameters: Once the asset geometries were fully incorporated into the models, we began identifying and sorting each component using shared parameters. Why shared parameters? For plenty of reasons! They ensure consistency of information across all Revit models, allow integration and scheduling of data from multiple files, and help manage spreadsheet and floor plan filters, among other benefits.

These are the main shared parameters we created:

• Asset Level: To assign the corresponding level where the asset is located.
• Asset Area: To specify the area it belongs to, such as chiller rooms, boiler rooms, or electrical rooms.
• Asset Name: To define the desired component name, independent of the Revit family name—for instance, AHU instead of Air Handling Unit.
• Asset Tag: To assign the unique identifier based on the facility’s internal systems.
• Asset # in Sheet: To determine the order in which the assets are displayed in each sheet or schedule.

*The use of shared parameters also helped us maintain control over element metadata and correct potential modeling mistakes, such as an asset modeled on the wrong reference level.

Step 2 - Master Revit Model: After generating and applying the shared parameters to each discipline model, we created a Master Revit model to centralize all metadata, schedules, and 2D documentation. This file acted as an empty container model, consolidating the 20-plus individual trade models along with their corresponding information and geometry.

Step 3 - Documentation: After establishing the master model, we proceeded to create sheets and schedules. This included generating 2D floor plans with appropriate filters to display and organize the assets within each area. We then placed the floor plans on the sheets and numbered all the assets using the tag annotation tool. Finally, we uploaded everything to Autodesk BIM360 for the site crew to start capturing asset names and tags.

Step 4 - Data Collection and Reconciliation: Equipped with all the documentation on their iPads, the site team began collecting asset names and tags (unique identifiers) and adding the information directly to the corresponding schedules and sheets. By using BIM360, the office team could view the markups in real time and promptly reconcile the data within the trade Revit models.

Step 5 - COBie: Once we identified and properly tagged all assets described in Step 4, we handed over our models to the FM team to extract the data and populate the COBie spreadsheets.

According to the US National BIM Standards, COBie (Construction Operations Building Information Exchange) is a specification designed to provide building owners with a standardized structure for organizing data. With COBie, owners can efficiently populate their facility maintenance systems to manage and maintain assets quickly and accurately.

As per our scope of work, all asset attribute information was to be consolidated directly into the COBie deliverable. The Revit models retained asset names and unique identifiers only, becoming the 3D link between COBie and the site.

The Challenges

I’d be lying if I said this process was easy—it wasn’t. This project posed challenges on multiple fronts, particularly due to its immense scale and the limited availability of our client. It required strong management and organization to ensure nothing was overlooked. The data collection process proved far more complex than anticipated, but we approached it methodically and learned valuable lessons to refine future workflows.

Before wrapping up this article (and series), I’d like to address one final concept that’s essential to understand before starting any BIM for FM initiative: the Level of Development (LOD).

Level of Development (LOD)

According to the BIM Forum, the Level of Development serves as a reference that allows AEC industry practitioners to specify and articulate the content and reliability of 3D models at various stages in the design and construction process.

Our scope of work included delivering an LOD500 BIM model. You might be wondering: How much more detail was added? This topic is somewhat controversial in our industry. As outlined by the BIM Forum, LOD500 doesn’t necessarily represent a higher level of detail than LOD400. Instead, it indicates that the element’s geometry is based on observations of an existing item rather than the design of a future one. It reflects what has actually been constructed, including any modifications made during construction. Essentially, it means “field verified”.

In addition, an LOD500 model should include non-geometric data, such as system information, serial numbers, specifications, warranties, and other maintenance details. The amount of data that can be added to the models is virtually limitless, making it crucial to define the scope of work clearly and adhere to it.

As I mentioned in my article ‘Scoping Laser Scanning Projects Like a Pro’, the scope of work should include all the work—and ONLY the work—to be performed. Properly defining the scope helps avoid countless hours of unnecessary data entry and prevents the creation of overly complex, heavy models filled with details that don’t add value to the project.

Final thoughts - The Digital Twin Buzzword

The term “Digital Twin” has gained significant traction in the AEC industry recently. However, I’d like to clarify that the models we created for this project don’t fully align with that definition. Our scope of work was not aimed at delivering a fully realized Digital Twin; rather, it represents an important first step on that journey. While we included system and asset names along with unique identifiers in our Revit files, these elements alone don’t constitute a complete Digital Twin. This project serves as a real-world example of applying reality capture technology to as-built an existing facility, laying the groundwork for what could eventually evolve into a comprehensive Digital Twin as we continue integrating more data over time.

You made it to the end. Throughout this Reality Capture journey, I’ve tried to highlight the vital role of effective project management in large-scale BIM initiatives like this one. As mentioned multiple times, successfully managing a project of this scale demands meticulous organization, clear communication, and a strategic approach to data collection to keep everything on track.

Thank you for following along! I hope this series has shed light on how BIM, reality capture technology, and project management can be applied effectively to large-scale AEC projects.