The rise of the Digital Twin: Why the enterprise needs to take notice

New research from Deloitte suggests that the enterprise should not ignore the benefits Digital Twin technologies have to offer.

When corporations wish to revamp their supply chains and gain more visibility into the everyday workings of their business, Digital Twin technologies can provide the solution.

The emergence of the Internet of Things (IoT), sensors, edge computing, and wireless technologies have made the concept of the Digital Twin viable, not only in terms of finance but also when it comes to data collection and analysis.

Digital Twin technology is the concept surrounding the creation of a digital "twin" or replica of a physical asset.

One asset may not seem important, but given the opportunity to create a digital version of a business' full set of assets and equipment, Digital Twins can provide valuable, actionable insight into operations and supply chains.

Rather than tinker with physical equipment, for example, information pulled from IoT sensors can be used to create a virtual replica for the purpose of experimentation.

Digital Twins can help businesses discover ways to improve operations, design, and test products -- before fully investing in them -- without causing disruption or failures in the supply chain by tampering with physical systems.

According to Gartner, 48 percent of enterprise players which are already employing IoT are using or plan to use Digital Twin technologies by the end of 2018.

The implementation of Digital Twin technologies is not a small project and must be considered in conjunction with the return on potentially high levels of investment. However, according to a new report issued by Deloitte, the technology is quickly spreading across industries including aerospace, retail, healthcare, and more.

"Companies are using these "Digital Twins" in a growing number of industries, making it easier to design and operate complex products and processes ranging from wind turbines to supermarket aisles," Deloitte says. "Digital twins are accelerating product and process development, optimizing performance, and enabling predictive maintenance."

According to the report, the global market for Digital Twin technologies is expected to grow to reach $16 billion by 2023, while the technologies that underpin the movement -- such as IoT and machine learning deployment -- are predicted to almost double by 2020.

See also: Cutting through the noise and defining the value of the Digital Twin for your business

The main industries that Digital Twin technologies are appearing to experience the most growth in are asset-heavy businesses, including manufacturing, oil and gas, aerospace, and the automotive fields.

However, Digital Twin technologies are also being utilized in retail, healthcare, and smart city pilot schemes.

Deloitte has outlined a number of new use cases in which Digital Twin technologies are being utilized. Some of the most interesting cases are below:

  • Maserati: The automaker is using Digital Twin technologies to accelerate product design. Virtual modeling and simulation are reducing the number of expensive, real-world prototypes required, as well as the need to launch physical wind tunnel tests and test drives, cutting vehicle development time by 30 percent.
  • Intermarché: The French supermarket uses data from IoT-enabled shelves and sales systems to create a digital twin of brick-and-mortar stores, enabling managers to get real-time insight on stocks and test the efficacy of different store layouts.
  • GE: The tech giant is using digital twins to model supply chain and factory processes at its Nevada facility in order to improve inventory management.
  • Dassault Systems: The healthcare company is building a library of realistic human heart simulations that physicians can consult to better understand a patient's condition in real-time.

Together with the support of tech giants including IBM and SAP, it may now be time for enterprise players at large to take notice of Digital Twin technologies.

"Digital twins can profoundly enhance an enterprise's ability to make proactive, data-driven decisions, increasing efficiency and avoiding potential issues," Deloitte says. "And they can make it possible to "experiment with the future" by exploring what-if scenarios safely and economically."

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