On-Demand Webcast
From Industrial Data to Digital Twins: Improving Asset and Project Performance
See how connected digital twins bring engineering, operational and enterprise data together to give industrial teams a clearer, more actionable view of their assets.
Industrial organizations manage critical asset information across engineering drawings, 3D models, maintenance systems, operational platforms, sensors, ERP systems and documents.
The challenge is not a lack of data. It is connecting that data around the asset so teams can find the right information, understand what is happening and act faster.
In this webcast, Markus Sukkinen, Asset & Project Performance Consultant at Cadmatic, and Johan Krebbers, CTO at Acuvate, demonstrate how Cadmatic eShare and Acuvate’s Data & AI capabilities can create a connected digital twin across the asset lifecycle.
What You’ll Learn
- How to connect engineering, operational, maintenance and enterprise data around physical assets
- How Cadmatic eShare creates a visual digital twin using 3D models, P&IDs, documents and asset information
- How to bring together data from ERP, CMMS/EAM, SCADA, historians, IoT sensors and other industrial systems
- How AcuPrism, AcuSignal, DiagramIQ and ontology services help connect and contextualize industrial data
- How AI, machine learning, GenAI, copilots and AI agents can work on top of connected asset data
- How digital twins can support asset management, maintenance, project handover and operational decision-making
From Disconnected Systems to Connected Asset Intelligence
A single industrial asset can have information spread across drawings, maintenance records, sensors, operational systems, manuals and enterprise applications.
A connected digital twin brings these sources together using the asset itself as the common context.
Teams can select an equipment item—such as a pump, compressor, turbine or production line—and access its related engineering information, operational data, maintenance history, documentation and AI-driven insights from one connected environment.
What You’ll See in the Webcast
See how Cadmatic eShare provides a visual environment for navigating industrial assets, engineering data, P&IDs and 3D information.
The session also explores how Acuvate connects the wider industrial data and AI ecosystem through:
AcuPrism — Enterprise and industrial data integration
AcuSignal — Industrial asset intelligence
DiagramIQ — Intelligent engineering drawings and P&IDs
AcuCortex & Ontology Services — Connecting assets, data and business context
AcuTrust — Data and AI governance
AcuNow — Real-time industrial and operational intelligence
Copilot, Power BI and AI Agents — Turning connected information into insights and actions
Together, these capabilities help create a digital twin that is not simply a 3D model, but a connected intelligence layer around the physical asset.
Why Watch?
If your teams still need to move between multiple systems to understand an asset, investigate an issue or prepare for maintenance, this session shows what a more connected approach can look like.
Learn how digital twins can help industrial organizations:
- Reduce time spent searching for asset information
- Improve visibility across engineering and operations
- Support predictive and proactive maintenance
- Improve project-to-operations handover
- Give teams faster access to operational context
- Build a stronger data foundation for AI and automation
Industrial AI - FAQs
An industrial digital twin is a connected digital representation of physical assets that brings together engineering, operational, maintenance and real-time data to provide a more complete view of asset performance.
Digital twins help teams access connected asset information faster, identify issues earlier, improve maintenance planning and make better-informed operational decisions.
Digital twins can connect data from 3D models, P&IDs, ERP, CMMS/EAM, SCADA, historians, IoT sensors, documents and other engineering and enterprise systems.
You’ll see how Cadmatic eShare and Acuvate’s Data & AI capabilities connect fragmented industrial data to create actionable digital twins for asset and project performance.