The Rise of Edge-Enabled Digital Twins in Industrial Environments
- Last Updated: March 14, 2025
Barbara
- Last Updated: March 14, 2025
Digital twins, the virtual replicas of physical entities, are revolutionizing industrial environments by enabling enhanced monitoring, simulation, and optimization of assets and processes.
Digital twins are gaining traction, yet adoption remains a challenge, especially in energy, water, and manufacturing. Gartner reports that while 13% of IoT-enabled organizations use digital twins, 62% are still in development. The main roadblock? Cloud dependency. High costs, security risks, and slow response times make cloud-based solutions less viable. The solution? Edge-Enabled Digital Twins.
Most digital twin platforms are cloud-oriented, which poses problems for these sectors. Concerns about cost, data privacy, security, and processing response times make cloud solutions less appealing. A recent study by Citrix revealed that 25% of organizations surveyed in the United Kingdom have already moved half or more of their cloud-based applications out of the cloud.
The reluctance to embrace cloud-based solutions opens up an opportunity for a new category of digital twins: Edge-Enabled Digital Twins.
These solutions operate independently of cloud infrastructure, maintaining data privacy and sovereignty while providing real-time data analytics and asset control. Edge computing allows processing to occur very close to the physical location of data source thus, minimizing latency and enhancing the security of the whole Digital Twin infrastructure.
Edge-enabled digital twins offer significant advantages in industrial environments where real-time decision-making and immediate feedback are critical. For example, in process manufacturing, they enable the immediate detection and correction of anomalies, preventing costly downtimes. In water infrastructure, real-time monitoring and control of chemicals ensure efficient resource management and compliance with regulations.
Edge-enabled digital twins offer significant advantages in industrial environments where real-time decision-making and immediate feedback are critical.
- David Purón, CEO at Barbara.
Relevant KPIs for industrial digital twin projects include:
Implementing a digital twin requires a multidisciplinary team comprising experts from both, Information Technology (IT) and Operational Technology (OT) domains.
IT professionals bring expertise in data analytics, cybersecurity, and edge software orchestration, while OT experts provide deep knowledge of industrial processes and systems, as well as integration with assets in the field. However, it is crucial to involve external technology experts as part of the team.
A common misconception is that organizations can manage digital twin projects entirely in-house using open-source software. While this approach may appear cost-effective initially, the Total Cost of Operation (TCO) for these projects can be significantly higher, up to 500% more over a three-year product lifespan, due to complexities in integration, maintenance, and scaling.
External partners bring specialized knowledge, products, and experience that can streamline the implementation process, mitigate risks, and ensure the Edge-Enabled Digital Twin solution is robust and scalable. David Purón - CEO at Barbara
The industrial sector stands on the brink of a digital revolution with the advent of digital twins. While challenges exist, particularly concerning cloud dependency, the rise of Edge-Enabled Digital Twins offers a promising solution.
By focusing on a reliable industrial-oriented edge computing infrastructure to provide real-time analytics and asset control, and leveraging a multidisciplinary team of internal experts and external partners, industrial organizations can harness the full potential of digital twins with no risk to their business continuity and security.
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