By Magdalena Ordyniec, M M.Sc., CanBIM CP; Founder & CEO of GET-TECH Innovative Solutions
This article references Get-Tech’s development of a Digital Twin Viewer — Flair3D — which is designed to help utilize the Digital Twin technology in design, construction, and operation. Knowing the pain points in the industry, Get-Tech has focused on enabling features that do not require heavy knowledge of the back-end technology, but simple and intuitive data search and visualization on the cloud, including BIM data, scheduling data, FM data, Scan data, and IoT data. Thanks to the Flair3D viewer, integrating BIM and IoT sensor data, many industry challenges can be minimized. Visualizing remote design, construction, and operations of buildings in one centralized location improves communication and collaboration.
BIM technology may have opened the first door of opportunities for the AECOO industry, but it is the introduction of Digital Twins and the Internet of Things (IoT) that offer even more unique values to discover another level of sophistication.
A Digital Twin is a “digital replica” of physical assets, processes, and systems integrated with sensors and software analytics, that represent near real-time status and condition; not only is it a 3-D design existing within virtual construction, but actual replication of a living organism such as an occupied building.
With the common issue of storing and sharing of data in all phases of construction — design, building, and operation — problems of complicated workflows, disconnected information, limited software functionality, and inefficiency are ever-present. Digital Twin technology is the key to helping with the problem of information, productivity, and quality loss. A centralized asset information repository can be created thanks to BIM, FM (Facilities Management), and IoT integration; the quality can be improved through the utilization of IoT apps monitoring deficiencies; productivity issues can be tackled through site monitoring tools, computational design, robotics, and machine learning; material waste can be reduced by implementing digital fabrication and modular construction based on data derived directly from the Digital Twins; finally communication can be enhanced thanks to collaborative platforms like online viewers visualizing 3D models, real-time sensor readings and data analytics.
Digital Twin technology is able to address the discrepancy between strategic planning ambitions and actual results. A good Digital Twin forms an expectation of the “results” side of things, creating possibilities to simulate various kinds of results by adjusting parameters so that there hardly be any surprises when executing the results in the real world. For example, there are cases of projects running as much as 80% over budget and taking 20% longer to finish than planned; Digital Twin technology has the potential to improve the entire construction industry’s performance and the entire life cycle of the built environment, through diverse solutions targeting specific problems.
Firstly, in the design phase, which is approximately 5-10% of the total cost of any building project, the advantage of Digital Twins is the ability to analyze and influence the outcome early and where changes have minimal impact to the overall project. For example, HVAC systems in a building are sized to best perform depending on the curvature of the building. During the design phase — and even construction phase, a building’s area, footprint, room layouts, etc, may change. This affects the sizing of the HVAC equipment within. A Digital Twin can simulate the different associated changes within the system and advise through, for instance, a flow analysis, as to what duct sizing is required to perform up to the standards. Such simulations are just one example of how to ensure the requirements can be achieved.
To minimize discrepancy between strategic planning/ambition and actual results we should focus on fixing one problem at a time with the best possible solution available at this moment. However, since interoperability is key, all of the tools — although working independently — must integrate with each other to be able to transfer the information back and forth and use it to achieve their specific goals. It is as if each problem is an empty space in the puzzle; each puzzle piece is a solution to a specific problem, and all the solutions are interconnected with each other and required to achieve an entire picture, or fully functional system as a result.
The simulation and behavior of objects in the virtual space is a big advantage of Digital Twins before they make their way into reality. Should they stay in the virtual space, the ability to morph, adapt, and simulate is by far superior compared to real objects and their behaviors. This of course influences efficiency and affordability from a management and commercial perspective.
Financial funding and return on investment in construction and real estate is one of the major challenges in technological advancement. We need to educate our users more on how to measure and achieve ROI, by comparing the upfront cost of software & hardware development, installation, and implementation with the long-term benefits which can’t be seen right away but can easily be predicted.
As each Digital Twin is different, the financial impact is different. However, the cost of the Digital Twin can be analyzed in a few stages: cost of the creation of the twin and cost of the maintenance of the twin. The cost of the creation is the main portion of the investment. The value of both stages depends on the purpose of the Digital Twin, its size, complexity, amount of available data, and required technology including software and hardware that needs to be deployed. If the available data is limited or outdated, the cost can increase by adding the data collection and processing cost.
Here is an example of our IoT Digital Twin to summarize the costs: the purpose of the Digital Twin was to remotely visualize all construction workers locations to enhance health and safety, improve productivity, and minimize labor cost. The Twin size is represented by a structural BIM model of the 340m high, 81 storey world-class skyscraper, and its complexity is equivalent to the issued for construction model (LOD 300). All of the 3D data to create the Twin was easily available in this case, as we used the georeferenced BIM models from the consultants and just imported them to the Flair3D viewer. In terms of technology, besides the initial monthly cost of the SaaS platform Flair3D we should add a one-time cost of the IoT system integration and the installation of the fixed IoT site sensors network as well as the wearable sensors for the workers.
In terms of the maintenance of the Twin, its value comes from the cost of the maintenance of the deployed technology for a certain time duration. In our example, the complexity of the 3D model was evolving during construction, so the Twin was updated to show the real conditions, which adds to the cost. Finally, the regular monthly software plan, including the data storage and analysis features as well as any necessary hardware maintenance, was included in the total fee.
In terms of the ROI, Dodge Data and Analytics states that 82% of BIM users reported a positive ROI on BIM technology, which also applies to the Digital Twin utilizing BIM. ROI can be calculated by comparing the costs associated with creating and maintaining the twin against savings generated over the life of the twin.
A case study provided by our IoT partner revealed that the utilization of IoT sensors on-site to leverage information and make decisions led to a 5% reduction in labor costs by streamlining queues and daily time savings of 30 minutes per worker, which inherently increased productivity. Coupling that with the savings from the resources not required on-site because of the remote site monitoring in Flair3D and time, savings coming from the 3D-enhanced scheduling (4D), decision making, and minimized response time; we are going to come close to 20% cost savings thanks to Digital Twin technology.
Based on the estimate of the Digital Twin’s impact on the cities, buildings, and infrastructure provided by Cities Today this technology may help to achieve a 35% cut in maintenance and operating costs and a 20% boost in productivity, with an overall estimate of US$280 billion by 2030 in cost benefits from using Digital Twins for more efficient urban planning.
Digital Twins provide a myriad of means and methods to analyze and monitor the living building, from the very moment it was created as a sketch on a napkin to the moment it ends its life in a pile of debris. In the meantime, this technology can enhance design, workflows and communication, minimize the cost and time of construction and operation, ensure the project is safer and better suited to serve its purpose, monitor and test performance at every stage of the life cycle, and efficiently store, update, and share the data from the centralized location, where it will never get missing.
To maximize the potential of Digital Twins we should look into the future. We expect that the full Digital Twins technology adoption in construction will happen within the next 5-10 years, considering the Metaverse development. Hypothetically, once that becomes reality, it could boost the Digital Twin market immensely as almost everything which already exists in virtual space will become part of it eventually. There are endless possibilities to grow and thrive, leading us into the next evolutionary step of the Digital Twins technology: fully automated design possibilities using integrated AI technology with only minimal human interaction, but maximum authority of final decision making.
