Plant Twin: From legacy equipment to a Connected Digital Ecosystem
Digital transformation in industrial settings is no longer just about upgrading equipment with the latest technology, it's about creating a connected, intelligent ecosystem that integrates people, processes, and technology to improve safety and throughput.
The Plant Twin, developed in collaboration between Spartan Scanning Solutions and Geminum and leveraging the NVIDIA ecosystem, is at the forefront of this revolution. This blog post explores how the Plant Twin modernizes legacy systems, integrates disparate technologies, and enables AI-driven operations.
The Journey to Autonomy: From Standalone Machines to Twin Ecosystem
The Plant Twin methodology enables a stepwise evolution from isolated, manual equipment to a fully integrated digital twin ecosystem. The diagram below visualizes this transformation for an example system, an overhead crane.
Evolution from stand alone equipment to ecosystem
Stepwise, we show:
Crane: A traditional, standalone machine with no connectivity
Connected Crane: Basic data connectivity for monitoring
Smart Crane: Enhanced with sensors and limited automation
Autonomous Crane: AI-driven, with minimal human intervention
Crane Twins + Plant Twin: Multiple cranes and operators are connected to a central digital twin platform, enabling real-time monitoring, operator-in-the-loop management, and predictive maintenance.
Twin Ecosystem: A network of cranes, operators, and legacy systems working collaboratively. Data flows seamlessly, enabling plant-wide and company-wide optimization, coordinated operations, and learning at scale that is driven back down to individual systems through software defined systems
This progression shows how digital twins not only enhance individual assets but also unlock new value when systems are integrated into a unified operational environment.
The Architecture: How Plant Twin Unifies Operations Across Systems
A true Plant Twin is more than a collection of digital models, it’s a layered, integrated platform that connects every element of the plant, from legacy machines to modern software to people.
Plant twin ecosystem - Plant twin, System twins, Safety twin, Product twin, Environment monitoring
Plant Twin: Aggregates data from all system twins, orchestrates plant-wide workflows, and supports custom interfaces and integrations to existing and new software and models.
System Twins: Each major system (e.g., cranes, conveyors) is modernized and represented by its own digital twin, allowing for targeted monitoring and optimization. Some systems need more modernization than others. System Twins are designed to enhance the value of standalone systems, and all twins feedback into plant-wide and class-wide monitoring and maintenance systems.
Safety Twin: Provides cross-plant safety monitoring and incident detection, providing near real-time situation awareness and feeding back into legacy safety systems.
Product Twin: Tracks products as they move through the plant, ensuring traceability and quality, and allowing system-of-system throughput improvements by identifying and predicting bottlenecks, and feeding back into legacy scheduling and maintenance systems.
Environment Monitoring: Continuously captures environmental data (people and vehicle movements, temperature, air quality) and integrates it into situation awareness and safety twin.
This architecture supports both centralized intelligence (for analytics and optimization across Plant and across the organization) and decentralized execution (with edge computing and local autonomy), delivering a flexible yet unified operational model. The move to software-defined systems also enables upgrades to control systems, scheduling tools, and predictive fault and maintenance tools to be pushed down to individual systems and across multiple systems.
Use Cases and Benefits
Modernization:
System twins lift legacy systems to new standards and normalize data to enable advanced monitoring & management of classes of equipment. This involves hardware and software and business process changes, not just “analytics”.
Safety:
Detect potential safety issues, simulate hazardous scenarios, predict risks from planned and emerging work, and create virtual training environments.
Production:
Optimize throughput, identify bottlenecks, simulate production changes, and improve process efficiency without disrupting operations.
Maintenance:
Enable predictive maintenance, reduce downtime, and schedule repairs proactively.
AI Adoption:
Enable safe sandboxing and simulations of new models and tools before rollout and compare legacy tools to AI models in production, to give users agency over how and when AI is used, and to give tech teams feedback on when AI is and isn’t used.
Key Technologies and Data Integration
Plant Twin leverages the NVIDIA ecosystem for a robust, scalable solution, upon which Geminum has built the unique use case-specific tools:
Twins: Enable collaboration and interaction across teams and systems and user activity measurement of feedback to AI tools.
Omniverse: Provides powerful, real-time visualization.
Isaac SIM: Facilitates simulation and AI training.
AGX/Orin/Fleet Command: Brings edge computing for real-time control and analytics.
Spartan Scanning brings expertise in reality capture and sensors, hardware modernization and experience in manufacturing and recycling.
Together, we provide the hardware, software, models and domain expertise needed to move manufacturers into the AI age.
From Automation to Autonomy
Traditional approaches to system automation and enterprise digital transformation often fail to deliver lasting value, especially at the plant and product level. Plant Twin’s connected ecosystem approach modernizes individual systems, integrates environmental monitoring, and digitizes workflows - enabling manufacturers to make the journey from simple automation to true operational autonomy at their own speed, and without huge investments into shiny technology that doesn’t improve overall system throughput.