The Evolution of Digital Twin – and How Emerging Tech Is Driving Adoption

The Evolution of Digital Twin – and How Emerging Tech Is Driving Adoption

A digital twin is a dynamic digital model of a product, process, or person, which analyzes existing business system data combined with real-world data. However, the value of digital twins expands past the single digital model of an asset and is increasingly an underpinning element of an organization's digital transformation initiatives.

There are innovative and emerging technologies spanning the digital twin stack creating tangible business value for smart connected products and smart connected operations use cases. However, each digital twin differs in some form of functionality, complexity, integrations and technologies. The more Technology systems added, the more ‘full’ the twin becomes, creating a digital thread, which adds challenges and opportunities for enterprise adopters and technology providers alike. Fundamental technologies up-through emerging ones span the physical and digital realms and enable increasingly valuable digital twin outcomes.

There are a few core underlying technologies to fulfill table stakes requirements of a digital twin, surpassing lighter digital replicas and shadow categorizations in terms of value created. The physical asset must have the compute power to generate data and access to servers on-premises, in the cloud or at the edge for further processing and storage. The means to transmit this data requires reliable connectivity, which can come in the form of a LTE cellular network for geographically dispersed assets or a private low-power wide area network (LPWAN) in an operations deployment, among others. Any form of connectivity and device with internet access requires prudent security systems ensuring the integrity of the device, network, data, and server. At some level, there must be an accessible digital definition of the asset’s historical systems of records, which could include computer-aided design (CAD) models, product lifecycle management(PLM) integrations and increasingly real-time characteristics.

As the digital twin matures, there needs to be another layer of control and actionability to truly satisfy its term; 451 Research claims that ‘Twin implies that what happens to one happens to the other, in a mutable fashion’. To fulfill this, an IIoT Platform is required to connect, contextualize, and interact with these disparate physical systems as well as provide the virtual lens of the digital twin equipped with real-time sensor data and predictive analytics. Equally important context come from enterprise-wide business systems integrations at the organizational (ERP) and factory floor (MES) levels. This twin data is made available to a variety of front-line personnel through HMIs, supervisory computers, and dashboards.

Emerging technologies will elevate digital twins’ functionality and related business impact in the near future.

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