What changed
AVEVA, in partnership with MIT Technology Review, has introduced digital twin technology that mirrors the dynamic behavior of industrial plants, allowing them to function like living systems. These 'living digital twins' provide real-time analysis and proactive interventions, moving beyond traditional simulation and observation to closed-loop execution. AI is central to this shift, enabling systems to adapt and evolve, much like organisms. The technology integrates engineering and operational data through a digital thread, linking assets throughout their lifecycle.
What this means in practice
The new AI-infused digital twins allow industrial systems to self-regulate, maintaining operational health through continuous adjustments. This capability, referred to as industrial homeostasis, helps keep plants running efficiently. Operators can now monitor AI actions and ensure alignment with defined operational standards. The technology also supports multiple lenses for analysis, such as sustainability, maintenance, and performance metrics. For instance, operators can assess emissions, asset health, or production output through these lenses.
Limitations and availability
While the technology is advancing, it remains in a developmental phase. Human oversight is still critical, as AI systems require guidance on what constitutes healthy operations. McGreevy notes that agentic AI is expected to follow a path similar to SCADA systems, with human involvement in supervisory roles. Full autonomy is limited to narrow, repetitive tasks. Additionally, governance structures are still evolving, with many organizations yet to establish comprehensive safeguards for AI decision-making. The technology is currently being implemented in various industrial settings, including refineries, chemical plants, and grid control rooms, with reported benefits such as energy savings and improved reliability.
