Digital Twin Technology: A "Flight Simulator" for Business
Perhaps the simplest explanation for digital twin technology is as a ‘flight simulator’ for business. Sophisticated flight simulators have been in use in the aircraft industry for some time, and anyone who’s seen the movie Sully saw them in action, with members of the National Transportation Safety Board recreating alternate scenarios for the pilot’s famous controlled crash landing on the Hudson which saved 155 lives.
The concept of a flight simulator for business is emerging, enabling managers and professionals to look across the systems and facilities within their enterprises, planning what-if scenarios, and viewing the impacts of real-time events. This simulation could involve digital twins of a technology infrastructure, an entire building, or a supply chain network.
Digital Twins in Various Industries
"We are seeing increasing adoption of digital twin technology across industries, but there are a few that are experiencing particularly rapid growth," Bill Quinn, futurist with TCS, told ZDNET. "For example, manufacturing and production is an area showing strong growth. The need for demand forecasting, inventory management, and real-time visibility into manufacturing processes make digital twins particularly attractive to this segment."
Quinn said the highest level of adoption of digital twin technology is still ahead of us: "Healthcare, mobility, and retail are the top areas expected to see the greatest adoption within the next three years."
Challenges in Implementing Digital Twins
While those developments are significant, the challenge is that implementing a business digital twin is not as quick and easy as implementing a piece of software like Microsoft Flight Simulator. These challenges were described in a recent paper published by Elsevier, in which the team of co-authors, led by Akram Hakiri of the University of Carthage, pointed out that "existing work on DT focuses primarily on the modeling perspective, and pays less attention to simplifying the control and management of industrial IoT networks."
Building a Digital Twin
"At a basic level, digital twins require IoT sensors, connectivity, modeling software, compute, and reporting tools," Quinn said.
The sensors measure the real-world person, or object, for which the twin is being created; the connectivity transmits the data collected by sensors to a central computer; the modeling software, aided by processing power, creates the digital twin within the central computer; and the reporting tools provide actionable outputs to the owners of the digital twin.
Enhancing Digital Twins with AI, AR, and 5G
In addition, Quinn said adding other technologies can enhance modeling and usability: "For example, AI will make it possible to run thousands or even millions of simulations on the digital twin to identify novel designs, use cases, or optimizations of the physical object. Virtual and augmented reality will create more realistic and immersive experiences of the digital twin. This is critical for users, such as maintenance technicians, surgeons, and product designers. 5G/6G and other advanced connectivity technology will allow digital twins to be leveraged in remote locations."
Digital Twin Maturity Model
To map out the route to digital twin development, the Digital Twin Consortium recently published a maturity model that identifies the stages of progress toward well-functioning digital twins:
1. Passive
- Vision and digital ambition: Lacking. "The need for a digital vision and strategy isn’t clearly understood at a senior level," the report states. There is "little or no awareness of digital technologies."
- UX and modeling: The authors suggest there is "post-reality monitoring and capturing," likely involving "sketched maps for design, no models of behaviors or dynamics."
- Technology integration: Are you kidding?
2. Starter
- Vision and digital ambition: "Some awareness of the need for a digital vision and of the major technologies that shape the industry."
- UX and modeling: "Physical entities modeled to have a similar visual appearance and rendered in 2D or 3D drawings or models. Processes modeled but only within silos and without any consistency across the business."
- Technology integration: There is "some integration between systems such as enterprise systems or collaboration platforms."
3. Progressive
- Vision and digital ambition: "Aware of the broad technologies that shape the industry including digital twins but not clear on the business outcomes."
- UX and modeling: "Quasi-real-time monitoring and capture — only within the constraints of how real-time the data is modeling of behaviors and dynamics."
- Technology integration: "Linked interactive data, especially common data: GIS, BIM, IoT data, Systems data, etc. Flow of data unidirectional and bidirectional with real-time analytics."
4. Mature
- Vision and digital ambition: "Understand the impact and importance of digital twin technology with defined business outcomes but not making full use of its potential."
- UX and modeling: "Near real-time synchronized, federated, and interactive operations using digital thread (two-way integration and interaction). Visualization and simulation are incorporated into the models."
- Technology integration: "Frequency of synchronization between systems are predictable and deterministic. Connected and interoperable systems using System of Systems."
5. Master
- Vision and digital ambition: "Digital twin technology is used to shape and continue to update and communicate the vision and achieve business outcomes."
- UX and modeling: "Autonomous operations and maintenance. Real-time synchronization — that is defined by the use case."
- Technology integration: "Data in the business context is linked throughout the lifecycle — upstream and downstream. Communication protocols allow for interchangeable systems — exchange between a simulation and real system or between different systems."
Conclusion
Digital twins will evolve gradually as standards and business cases coalesce. You can’t go from here to there without building foundational digital competencies.
FAQs
Q: What are the challenges in implementing digital twins?
A: Implementing a business digital twin is not as quick and easy as implementing a piece of software like Microsoft Flight Simulator. There are several challenges, including security risks, need for new business models and practices, and prohibitive complexity with network deployments.
Q: What are the benefits of digital twins?
A: Digital twins can provide real-time visibility into manufacturing processes, enable demand forecasting and inventory management, and optimize supply chain networks.
Q: How do I get started with digital twins?
A: Start by identifying the areas where digital twins can bring the most value to your business, such as manufacturing or supply chain management. Then, assess your current technology infrastructure and identify the necessary upgrades or changes to support digital twin implementation. Finally, develop a clear plan and timeline for implementation, and secure necessary budget and resources.
