Digital Twin: Bringing MEP Models to Life

What Is a Digital Twin?

“Digital twin is a set of virtual information constructs that fully describes a potential or actual physical manufactured product from the micro atomic level to the macro geometrical level.” — Michael Grievers

Historic Digital Twins

Looking back to see where the digital twin concept came from, one can look to NASA in the 1960s during the first trips to the moon. NASA built exact replicas of everything that was launched into space. During production these replicas were prototypes of the actual objects, and after the objects were on their way to remote destinations, they became a twin of the equipment in use. All modifications made by the astronauts on their way into space were also made to the twin. This is probably best documented during the ill-fated Apollo 13 mission to the moon where there was a serious malfunction in the service module two days into the journey. Before mission control sent instructions to the astronauts, simulations were made to what we could call an “Analog Twin” to simulate all decisions made before implementing them on the physical object thousands of kilometers away. This is known as a Mirrored System since physical modifications were made to a twin physical object even though there were digital calculations made as well.

Creating a Digital Twin

When creating a digital twin, the system needs to be planned from the beginning rather than imposed on a project at a late stage. The data required, how the data is generated, how the data is received, how the data is stored, who has access to the data, and the types of digital models required must be planned. After the framework is in place, then the technology to be integrated can be selected for the physical asset to enable the capture of the real time flow of data.

Evaluating Behavior

Digital twins can help prevent serious accidents by the real time monitoring of the physical asset. By combining 3D scanning and sensors there is the opportunity to monitor existing assets where a digital model has not been created.

System Lifecycle

During the system lifecycle, there are two flows of data. The first is by the creation of the physical system where data flows forward as traditionally from creation to production to operation to disposal. However, data for a digital twin flows in reverse. Data from the future phase informs the previous stage. This data can be used to improve the performance of the systems by finding the weaknesses and failures that need refinement.

The Value of the Digital Twin

The value of the digital twin lies in the data and its connection from the physical system back to the virtual system. Large amounts of data can be generated which is used to inform design and operational decisions. It is important that the data created is reviewed and analyzed to gain greater understanding of the environment that will be affecting the physical system. Data replaces wasted physical materials, time, labor, and energy over the lifecycle of the system. Data is never free to acquire. It will require resources such as planning, implementation, sensors, software storage, and time. The cost of acquiring data is less than the cost of the physical waste operating an underperforming system. The greatest gains are made during the creation stage this reduces the amount of trial and error during the production phase. For MEP projects digital twins can improve the performance of systems, improve indoor environment, reduce energy consumption, and reduce operation cost.

Issues with Data

There are still security risks associated with digital twins. Typically, the data is stored in the cloud, so there is no physical infrastructure associated with the data storage side. However, there is a massive amount of data being collected from endpoints. Each of these endpoints are a potential point of weakness in the system. There is a possibility that data can be compromised between the endpoints and the cloud. Users of the data should have defined roles and it is best if the information transmitted is encrypted. The devices must have rights to send data over existing IT infrastructure.

Our Process

We were inspired by Project Dasher and the Autodesk bridge project at Pier 9. The idea of linking sensors and models became the goal. After a call with Kean Walmsley we quickly found out that we would need to change our strategy. Getting the project into Project Dasher would not be as easy as we originally had hoped. We also saw the cabling challenges that the bridge project exposed, so we wanted to go wireless. From here we embarked on our digital twin journey.



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Aashish Mathew George

Aashish Mathew George


Entrepreneuring | curious thinker | technology advisor | photographer at stories by AMG | CTO of paradigm IT |