As the enterprise adopts Internet of Things (IoT) technologies to collect and use information, revamp supply chains, and gain more visibility on the factory floor, the concept of the Digital Twin has also caught corporate interest.
Digital Twin technologies revolve around the idea of creating a digital counterpart of a physical asset.
While the concept has been floated for years, it is only since the introduction of IoT -- and all the sensors, networking, and Big Data that may be included -- that the Digital Twin has become a financially viable concept to implement.
Enterprises can use IoT endpoints to construct a virtual replica of their physical systems and assets and use this model to analyze current business operations, make changes, discover errors, and optimize processes without the need to tamper with physical objects.
This, in turn, makes the technology cost-effective and particularly useful for industrial players.
Digital Twin may be in the early stages of implementation, but according to research agency Gartner, almost half of enterprises are keen to experiment with the concept.
On Tuesday, Gartner revealed the results of a survey which suggests that 48 percent of companies which are already enjoying the benefits of IoT are using, or plan to use Digital Twin by the end of 2018.
The survey, which included 202 respondents from organizations in China, Germany, Japan, and the US, also indicated that the there is the potential for enterprise use to triple by 2022.
In addition, the research firm estimates that by 2020, at least 50 percent of manufacturers with annual revenues of at least $5 billion will have at least one Digital Twin initiative launched for either products or assets.
However, Digital Twin technologies are not for the faint-hearted as it can pose significant challenges for the enterprise.
Implementation has to be unique to each organization and converging existing data, including information gathered from IoT, into a scalable model is not easy. Bringing third parties from supply chains into the mix -- required to create a full picture of product life cycles -- can also be difficult.
Gartner suggests that Digital Twin investments should be focused on boosting the supply chain, however, for the best financial rewards. Digital Twin-based machinery and product management can improve visibility, be used for predictive maintenance, and prevent untimely disruption.
"The value of Digital Twins can be an extensible product or asset structure that enables addition and modification of multiple models that can be connected for cross-functional collaboration," the agency notes. "It can also be a common reference with comprehensive content for all stakeholders to access and understand the current status of the physical counterpart."
In addition, Gartner suggests that modeling practices, including data from multiple sources, and avoiding proprietary Digital Twin software can improve the overall longevity and performance of Digital Twin systems.
"There is an increasing interest and investment in digital twins and their promise is certainly compelling, but creating and maintaining digital twins is not for the faint-hearted," said Alexander Hoeppe, research director at Gartner. "However, by structuring and executing digital twin initiatives appropriately, CIOs can address the key challenges they pose."