Future PRINTer

When XR Meets the Factory Floor

Integrating Digital Twin and Extended Reality
into a lithography production line

Digital Twin Extended Reality IoT / IIoT AI & ML

Greek R&D Project · 2024–2026

Bridging Physical and Digital in Modern Manufacturing

Future PRINTer is a 24-month R&D project developing a fully integrated platform that digitally mirrors a lithography production line and makes that mirror accessible through Extended Reality.

The project unites two partner organisations — a technology research company and a lithography production company — bringing together expertise across software engineering, extended reality, AI/ML, and real-world print production operations.

2Partner Companies
4Key Technologies
FP
IoT Sensors
Digital Twin
AI / ML
XR App

Core Technology

Four Pillars of Innovation

Each layer solves a distinct real-world problem on the production floor

Digital Twin

A real-time virtual mirror of the production line. Sensor data updates the model continuously, enabling simulation, what-if analysis, and anomaly detection without touching the real machine.

  • 3D machine models
  • Live sensor data binding
  • Process simulation
  • Optimisation loop

Extended Reality

AR overlays and VR simulations put digital information directly in front of the operator — for immersive training, live operation assistance, and step-by-step maintenance guidance.

  • VR training scenarios
  • AR operation overlay
  • Maintenance guidance
  • Knowledge preservation

Sensor Network

Raspberry Pi IIoT nodes deployed across the production line, capturing temperature, vibration, pressure, light, and motion in real time via MQTT to the data platform.

  • 6+ sensor types per node
  • MQTT data streaming
  • SQLite local resilience
  • Systemd always-on service

AI / ML

Machine learning models trained on multi-sensor time series to predict faults, classify machine state, detect anomalies, and project the health trajectory of components.

  • Fault prediction
  • State classification
  • Anomaly detection
  • Predictive maintenance

Extended Reality in Practice

XR Scenarios

Three distinct use cases, each solving a real operational pain point

VR Simulation

Training

New operators complete full simulated production runs in VR before touching the real machine. Zero risk, repeatable, and measurable skill assessment on demand.

AR Overlay

Operation Assistance

Real-time sensor readings and Digital Twin state overlaid on the physical machine. Colour-coded health indicators and anomaly alerts guide operators before problems escalate.

AR Guidance

Maintenance

Step-by-step 3D instructions guide technicians through repair procedures. Institutional knowledge is captured digitally, reducing dependency on individual experts.

The Companies Behind It

Project Partners

Two complementary organisations combining R&D expertise with real-world production know-how

digipath

Technology Partner

Responsible for software architecture, Digital Twin development, sensor network deployment, AI/ML algorithms, and Extended Reality application development.

FF

Production Partner

Provides the lithography production line, operational expertise, domain knowledge, and real-world validation throughout testing and field trials.

Latest Updates

Project News

Follow our progress as the project moves from research to real-world deployment

What We Deliver

Project Outcomes

Tangible results produced throughout the project — updated as work progresses

Acknowledgements

Funding & Support

Future PRINTer is co-financed by the European Union and Greek national funds through the Operational Programme Competitiveness 2021–2027 (ΕΣΠΑ – Πρόγραμμα Ανταγωνιστικότητα).