A digital twin (DT) is a simulation or virtual model of a physical object that accurately mirrors the structure of that object. The concept was first introduced in 2002, but the technologies needed to make the concept widely accessible have recently reached a tipping point. The convergence of key enablers such as, cloud, data storage, computing power, wireless networks, ML, AI, IoT and sensors are propelling DTs to the forefront as a critical tool for enterprise management.
Owning to these technologies, more sectors and application areas now recognise DTs as a way to build products and processes as they are becoming more detailed and predictive. For instance, cloud computing has led to wide availability of computing power required to run simulations and forecasts. Moreover, falling price of network-connected sensors is making it practical to monitor large objects in granular detail
Early DT leaders show the way
DT is not just a niche technological breakthrough, rather a key focus area for world’s largest technology firms – These companies not just have tangible solutions, but have been observed as being highly active in this space:
- Microsoft Corporation: Microsoft has an AI-based Azure Digital Twins platform that allows design of digital models and knowledge graphs. In Dec 2020, Azure Digital Twins was made generally available, offering ready-to-use building blocks to simplify the creation of comprehensive digital models
- General Electric (GE): GE has created the most advanced asset and process measurement DT that integrates analytic models. In Jun 2021, GE Digital announced the availability of a process analytics solution – Digital Smelter. It creates a DT of the aluminium smelting process to deliver additional insights and prescriptive guidance to help reduce raw material costs, optimize energy consumption and maximize production
- IBM: IBM Digital Twin Exchange for asset-intensive industries, which allows companies to virtually create, test, monitor, and build solutions to market product faster and make accurate predictions about product performance. In Aug 2021, IBM and Black & Veatch collaborated to expand the IBM Digital Twin Exchange using Black & Veatch’s DT asset models
A pragmatic approach to standardise digital twin
Though major US technology companies are leading the simulation race, industry collaborations and consortiums are helping standardise the architecture, security, and interoperability of DT:
- Digital Twin Consortium: Object Management Group’s (OMG) Digital Twin Consortium is a collaborative organization driving the DT innovation through consistent approaches and open source development. Some of the most prestigious organisations are its members: Dell, GE, Ansys, Microsoft, Bentley, etc.
2 https://www.arcweb.com/blog/microsoft-azure-digital-twins-now-generally-available
In Dec 2021, the Digital Twin Consortium and Industrial Digital Twin Association (IDTA) entered into a liaison agreement to create and develop DT enabling technologies, with an aim to propel the monetization and adoption of DTs
- IDTA: Since IDTA is a German consortium, above collaboration provides US technology leaders with a platform to have open discussion and share innovate ideas, with international developers and companies in the DT space. Since IDTA went live in March 2021, the number of members has almost doubled to a total of 45 companies
Sector specific adoption of DTs on the rise:
Companies across a diversity of sectors and application areas utilize DT to improve planning and decision-making, including manufacturing, supply chain, automotive, infrastructure (smart cities), oil & gas, healthcare, among others. DTs are being used in product design, development, machine & equipment health monitoring, process support, sales & services
- Building Smarter Cities: As cities continue connecting their urban environments, the concept of DT has entered the realm of smart cities and promises to enable city administrations and urban planners make more accurate predictions and development strategies
- In Feb 2021, Microsoft announced the open-source GitHub repository of Smart Cities ontology for Azure Digital Twins
- New York City, Las Vegas and Chattanooga are among the cities using DTs to map out their cities
- US start-up – Cityzenith has developed a DT platform SmartWorldPro to create a digital replication of infrastructure and buildings
- Complementing the Automotive Value Chain: Adoption of DT in the automotive sector is trending in areas such as vehicle engineering, design customization, manufacturing, and vehicle maintenance
- Ford has integrated a predictive DT technology within its Powertrain Manufacturing Engineering department as the foundation of its own customized platforms, known as the Ford Interactive Simulation Tool and Ford Assembly Simulation Tool
- Tesla Motors is also deeply invested in DT technology to provide better service and reliability for car owners
5 https://www.digitaltwinconsortium.org/cgi-bin/dtcmembersearch.cgi
7 https://industrialdigitaltwin.org/en/news-dates/number-of-members-doubled-1
9 https://www.globalconstructionreview.com/las-vegas-to-try-its-luck-on-a-city-wide-digital-twin/
- Efficient Industrial Manufacturing and Supply Chain: DTs footprint is growing across product development, operations management, predictive maintenance in the industrial manufacturing and logistics space
- Google launched Supply Chain Twin, a new DT solution to develop a representation of physical supply chain across sectors
- In Sep 2021, Ansys and Rockwell Automation partnered to expand DT to industrial control systems, enabling users to optimize the design, deployment, and performance of industrial operations
- Cost optimization in Oil and Gas sector: Prevailing downturn from COVID-19 has mandated the need to reduce costs, which has led to the increasing deployment of DTs in the natural resources sector:
- Chevron expects to save millions of dollars using DTs to predict maintenance problems efficiently
- ExxonMobil recently partnered with Kongsberg Digital to deploy Kognitwin Energy dynamic DT software that provides flow simulation and drives higher asset performance
- The Energy Department’s Idaho National Laboratory (INL) uses DT to develop next-generation nuclear reactors
- Digital defense and security:Alongside commercial industry, the federal agencies are also highly involved in the DTs for smooth and safer operations
- FedScoop reported that the US Air Force, through its Advanced Battle Management System is building DTs of its weapons systems
- Furthermore, all three military branches are exploring DTs to improve weapons platforms and systems’ readiness and maintenance18
- The Homeland Security Department is exploring DT to understand if US Customs agents can better track and mitigate risks associated with e-commerce shipments coming across US borders18
Emerging start-ups to grow competition and expand application areas:
With rising industry adoption, another measure of success for a technology is to understand the level of investor traction attained and the scale of growth presented by emerging start-ups. To explore this fact, a notable number of start-ups in the DT space have been identified as raising significant funding:
13 https://analyticsindiamag.com/google-cloud-launches-digital-twin-for-supply-chain-management
18 https://www.accenture.com/us-en/insights/us-federal-government/technology-vision-2021-digital-twins
19 https://www.fedscoop.com/air-force-builds-digital-twin-weapons-systems-abms/
| Date | Company | Funding (Mn) | Series | Description |
| Nov-2021 | Nexar | $53.0 | Series D | An AI-based tool that is being used to create a complete DT of US roads |
| Aug-2021 | Aforza | $22.0 | Series A | A DT model for packaged goods market raised capital to establish US headquarters |
| Jul-2021 | Lacuna | $16.0 | Series A | Capital raised to help cities build DTs to better manage and monetize transit networks |
| Jun-2021 | Mapped | $6.5 | – | Provider of a DT of data infrastructure APIs |
| May-2021 | Twaice | $26.0 | Series B | A DT platform for electric car raised capital for the US expansion |
A correlated outlook of digital twin:
The further adoption of DT will be directly correlated to the growth of AI, computing power and IoT. As diverse sectors and innovators convert these technologies into empirical solutions from concept, DT will eventually witness multi-fold growth as a bi-product. Growth will also be fuelled by the constant surge in complexity of future products and processes, wherein DT has the potential to simplify understanding of complicated architecture and provide a virtual solution to a problem
Source: Accenture, GlobalData, Deloitte, Industry Articles
