Digital Twin use cases are skyrocketing across industries. Here's why.

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 are finally here. Key enablers such as cloud, data storage, computing power, wireless networks, ML, AI, IoT, and sensors are making DTs highly desirable for enterprise management.

Plenty of sectors and application areas already have mature DT practices for building products and processes as they become more detailed and predictive. For instance, cloud computing has made the computing power required to run simulations and forecasts widely available. Moreover, the falling price of network-connected IoT 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 the world’s largest technology firms:

• Microsoft has an AI-based platform, Azure Digital Twins, that allows the design of digital models and knowledge graphs. In Dec 2020, it was made generally available, offering ready-to-use building blocks to simplify the creation of comprehensive digital models.
• General Electric has created the most advanced asset and process measurement DT that integrates analytical models. In Jun 2021, GE Digital announced the availability of a process analytics solution, Digital Smelter. It creates a DT of the aluminum smelting process to deliver additional insights and prescriptive guidance to help reduce raw material costs, optimize energy consumption, and maximize production.
• IBM Digital Twin Exchange for asset-intensive industries allows companies to virtually create, test, monitor, and build solutions to market products 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 standardize digital twins

Though major US technology companies are leading the simulation race, industry collaborations and consortiums are helping standardize the architecture, security, and interoperability of DTs:

Digital Twin Consortium: Object Management Group’s (OMG) Digital Twin Consortium is a collaborative organization driving DT innovation through consistent approaches and open-source development. Some of the most prestigious organizations are members, including Dell, GE, Ansys, Microsoft, Bentley, etc.

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, the above agreement provides US technology leaders with a platform to have open discussions and share innovative 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 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, and 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 to 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 notable 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. 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 to make more accurate predictions and development strategies.

Complementing the automotive value chain:

• Ford has integrated 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, according to Automotive Logistics.
• Tesla Motors is also deeply invested in DT technology to provide better service and reliability for car owners.
• The DT footprint is growing in the efficient industrial manufacturing and supply chain space across product development, operations management, and predictive maintenance.
• Google launched Supply Chain Twin, a new DT solution to develop a representation of a 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 the oil and gas 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, a 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:

• According to FedScoop, the US Air Force, through its Advanced Battle Management System, is building DTs of its weapons systems. In fact, all three military branches are exploring DTs to improve weapons platforms and systems readiness and maintenance. The Homeland Security Department is exploring it to understand if US Customs agents can better track and mitigate risks associated with eCommerce shipments crossing US borders.

Emerging start-ups to grow competition and expand application areas

Another measure of success for technology is the level of investor traction and scale of growth presented by emerging start-ups. To explore this, a notable number of start-ups in the DT space have been identified as raising significant funding:

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 witness big growth as a byproduct. Growth will also be fueled by the constant surge in the complexity of future products and processes, wherein DT has the potential to simplify our understanding of complicated architecture and provide a virtual solution to a problem.

As digital twin opportunities become more accessible, finding the right use case can be daunting. 

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