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How SFO's digital twin keeps construction data working after the project ends

San Francisco International Airport rehearsed changes in its $11 billion capital program in a digital twin before building them in the live terminal, helping airlines keep operating. SFO teams also developed an automated workflow that brings mechanical, electrical and plumbing BIM models into the airport’s enterprise GIS and digital twin so design and construction data carries forward into operations.

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By MarketScale Newsroom · San Francisco International AirportSfoEsriDigital Twin
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How SFO's digital twin keeps construction data working after the project ends

Key takeaways

01

An owner's operating digital twin is largely built from construction handover data: SFO now pipes mechanical, electrical and plumbing models straight into its enterprise GIS so project data keeps working after closeout.

02

Shared visibility did much of the work during SFO's $11 billion program: construction, operations, security and airline partners read one location-based model, so conflicts showed up as design questions instead of shutdowns.

03

Digital twin programs now have an external yardstick: the BSI Kitemark for Digital Twins, built on the BS ISO/IEC 30186 maturity model, grades governance, security, ownership and measurable value.

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Every phase of San Francisco International Airport's $11 billion capital improvement program touched something passengers rely on: a security checkpoint, a utility line, a baggage system, the route to the gate. SFO set out to do all of it while staying fully operational. Its method was simple to describe. Teams tried each change in a digital twin of the airport first, then built it for real.

According to a Forbes article on the project, SFO teams recently developed an automated workflow that integrates building information models into the airport's enterprise GIS and digital twin. The workflow covers mechanical, electrical, plumbing and other building systems as well as architecture. For anyone running a large campus, that step could be what keeps a capital program's data useful after the project closes.

Rehearsing construction in a live terminal

The airport's size explains why it rehearses changes first. Kewley calls it a hard version of modernization: no downtime, no spare capacity, and millions of people passing through every month. When one phase moves a checkpoint, the change can also hit utilities, baggage handling and passenger flow, and any of those can set off a chain of disruptions.

The airport the twin has to mirror

54 million
passengers a year moving through while construction continued
18 million+ sq ft
of indoor space modeled, from rooftop solar to underground utilities
100+ buildings
spread over eight square miles, all tied to exact locations
$11 billion
in capital improvements tested in the twin before construction

Forbes (Kathleen Kewley, Esri)

In Kewley's account, construction, operations, security and airline partners all worked from the same view. Issues that might have forced emergency shutdowns came up early, while they were still design questions. Airlines kept operating and passengers kept moving during the program.

This suggests most of the value came from shared visibility rather than raw simulation power. Moving a checkpoint is a security question, a utilities question and an airline question all at once. When all four groups read the same model, a conflict appears on screen before it appears in a concourse. Operators planning phased work inside a facility that never closes, such as a hospital, a distribution hub or a transit station, would face the same coordination problem.

Daily use is less dramatic. Josephine Young, SFO's director of infrastructure information management, calls the twin a "window of entry" for business units across the airport. Users can look inside a building layer by layer. Managers use it to plan a terminal remodel or a new link between baggage claim and public transit. It also handles preventive maintenance, down to when and where to change lightbulbs or upgrade pipes.

Why every data point carries an address

Kewley argues that without that geographic anchor, the model couldn't show how a passenger bottleneck in one area backs up a security checkpoint elsewhere, or how slow cargo unloading affects logistics inside the airport and beyond it.

Esri's architecture team made a related point the same day in an ArcGIS Blog post by Rob Elkins, Julia Colbert, Jay Fowler and Dylan Molnar. They cite the Digital Twin Consortium definition, which turns on a model kept in sync with the real world at a specified frequency and fidelity. They add two conditions people often skip: the twin needs a defined outcome, and people have to adopt it in real workflows. Their transportation example lists the feeds a twin like this can use, including vehicle location, vessel and aircraft tracking, traffic and weather. They also advise choosing data by the decisions the system has to support rather than by how many feeds exist.

That filter is practical for a facilities director scoping a twin. SFO's stated uses are concrete: a remodel, a transit connection, a lightbulb schedule. Each needs only a short list of data layers. Start with the decisions, and the data list comes out much shorter than a list of every available sensor.

Handover data that keeps working

The newest piece of SFO's twin is an automated workflow that brings BIM models into the airport's enterprise GIS. It covers mechanical, electrical, plumbing and other building systems as well as architecture. Kewley says the immediate gain is a fuller, continuously updated view of infrastructure. The larger one is that design and construction data carries forward into operations and asset management.

SFO teams recently developed an automated workflow that integrates BIM models into the airport's enterprise GIS and digital twin. It covers mechanical, electrical, plumbing and other building systems as well as architecture, so data from design and construction keeps paying off after the project ends.

For owners running long capital programs, that changes where the twin gets built. If MEP models feed the operating system directly, the twin is only as good as what contractors hand over. Owners would care about model completeness, consistent asset identifiers and accurate locations. MarketScale's read, not a published SFO requirement, is that these expectations belong in design and construction contracts written now, years before the equipment shows up on a maintenance schedule.

AVEVA reports that engineering firm AP Consultoria e Projetos used a cloud-based engineering environment where multidisciplinary teams worked from a single source of truth. The firm cut analysis time for pipe support type and position by 90% and reduced total project delivery time by nearly 50%. The post was first published by the Financial Times Tech for Growth Forum. The mechanism looks similar to SFO's: when every discipline works from one model, problems could surface earlier.

Where the word twin stretches

Not everyone uses "digital twin" the same way. In an Oct. 21 guide, Tributech CEO Thomas Plank cites a 2018 classification by Kritzinger and colleagues that separates three levels by how data flows between the asset and the model. Under that test, a model that receives data from the asset automatically is a digital shadow, and only one that also sends data back automatically counts as a digital twin. Operators could weigh their own planning uses against that line.

In the Kritzinger et al. (2018) classification, a digital model is updated by hand in both directions. A digital shadow receives data from the asset automatically, but changes go back by hand or not at all. A digital twin exchanges data automatically in both directions, so commands from the model can reach the physical asset.

That isn't a knock on SFO's results. It changes what a buyer should specify. For coordinating construction and planning maintenance, two-way control may not be needed, and it carries extra security weight: Plank notes that once a twin can write to an asset, it becomes part of the control path, and ISA/IEC 62443 security rules apply. For many facilities programs, a read-only twin is the safer and cheaper choice.

Two other problems Plank lists apply to any large owner. Models drift from reality as assets change, and ownership is often split among OT, IT and engineering. SFO's automated workflow that brings BIM models into its enterprise GIS and digital twin suggests one way owners could keep a model from drifting.

A yardstick for twin programs

Buyers now have an outside reference point. BSI announced the BSI Kitemark for Digital Twins in an Oct. 7 press release and called it a new certification scheme. Its purpose is to let organizations show that the digital twin capability they run is secure and well governed, and that it delivers measurable business outcomes. Further requirements are added on top for governance, competency, security, risk management and value realization. Assessment covers a specific twin as well as how well the organization can deploy, govern and improve twins over time. The first certification went to Neuron at a ceremony in Hong Kong.

Certification won't suit every program. Owners who are early in the process can still use the maturity model as a checklist. Together with SFO's example, it points to a few questions to settle before scoping a twin or writing it into a capital program:

  1. Which operating decisions will the twin support, and which data layers does each one actually need?
  2. How will design and MEP models enter the GIS at handover, and who keeps them current afterward?
  3. How often does the model sync, and does it only read from assets or also send commands back?
  4. Which team owns the model when OT, IT and engineering each hold part of it?

The next step at SFO is easier to measure. Kewley writes that as automation and AI improve, the twin should get better at flagging discrepancies and spotting patterns behind the scenes. If it starts surfacing problems that no one asked it to look for, it will be doing more than mapping the airport.

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