At the 2024 Industrial IMMERSIVE Week, Edward Martin from Twinsight Consulting shared his insights in a session titled "No Twin is an Island: A Relational View of Digital Twins." Martin presented a detailed, holistic perspective on the implementation and optimization of digital twins, emphasizing that digital twins do not function in isolation but as part of a broader system. Here are the key takeaways from his presentation.

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The Micro to Macro Journey

Martin began by focusing on how digital twins can represent the smallest components within a system. He used the example of a high-pressure valve, explaining how its digital twin incorporates data such as the serial number, inspection history, operational metrics like pressure and temperature, and even its physical location within a facility. However, as he pointed out, the real value emerges when these isolated data points are connected to form a comprehensive, system-wide view.

This micro-level perspective scales up to entire systems and facilities. The complexity grows exponentially as data from multiple components—each with its unique characteristics—is aggregated to form a more holistic view. At this facility-wide level, opportunities for operational efficiency and predictive maintenance are vast, but so are the challenges of integrating the data.

Optimizing Operations through Data

One of the most significant challenges Martin highlighted is the siloed nature of data. In many organizations, data from SCADA systems, asset management tools, and training platforms exists separately, preventing companies from realizing the full potential of their digital twins. By integrating these sources, organizations can optimize preventive maintenance schedules, make more informed decisions about equipment upgrades, and enhance safety protocols.

Martin offered examples of how digital twins can benefit businesses by simulating proposed operational changes, reducing risk through real-time AI augmentation, and providing more advanced training for technicians through immersive simulations. He also underscored the value of AI in digital twins, particularly in identifying patterns in large data sets that are difficult for humans to recognize.

Building Blocks for Digital Twins

Martin emphasized that digital twins are ultimately built on data—historical, live, and metadata. Effective data management and integration are critical to overcoming data silos and unlocking the full potential of digital twins. Beyond data, other essential building blocks include spatial data, time series data, behavioral models, simulations, and AI-driven insights. However, organizations don’t need to implement every building block at once; they should focus on what will drive immediate business value.

A Flexible Approach to Digital Twin Implementation

Martin advocated for a flexible and scalable approach to building digital twins, suggesting that organizations start with smaller projects that address specific business pain points before scaling. He cautioned against one-off, special-purpose digital twins, as they can lead to duplicated efforts and incompatible systems.

In conclusion, the promise of digital twins lies in improving operational efficiency, reducing risks, and empowering employees with better tools and insights. However, the journey begins with thoughtful data management and a clear vision for how to integrate and scale these systems over time. Martin’s advice, curated from others? “Think big, start small, and scale fast.”

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