As manufacturing becomes increasingly complex and customized, inspection processes must evolve just as rapidly. Traditional robot programming methods often struggle to keep pace with frequent product changes, shorter production cycles, and growing demands for precision.
Within the AI-MATTERS ecosystem, RoboDK partnered with ARENA2036 to explore how AI-enabled robot simulation and offline programming can transform industrial inspection workflows, and validate those capabilities in a real production environment.
The Challenge: Faster Commissioning, Greater Flexibility
RoboDK, a specialist in robot simulation, offline programming, and digital twin technologies, set out to address a critical industry bottleneck: the time and effort required to program and commission robots for inspection tasks.
While digital tools can simulate inspection paths and robotic movements, proving that these virtual models perform reliably on real industrial robots is essential. Without validation under real conditions, even the most advanced simulation remains theoretical.
To bridge this gap, RoboDK sought access to a realistic industrial environment where simulation-based inspection workflows could be tested and refined under operational constraints.
The AI-MATTERS Approach: Testing Beyond Simulation
Through AI-MATTERS, RoboDK gained access to the ARENA2036 research factory – a flexible and reconfigurable shopfloor designed to test next-generation production technologies.
This collaboration enabled RoboDK to:
- Validate offline-programmed inspection paths on real industrial robots
- Demonstrate accurate simulation-to-reality transfer
- Test inspection workflows in a dynamic, industrial setting
- Evaluate flexibility across different inspection scenarios
By moving from digital twin models to real-world validation, RoboDK demonstrated that AI-supported robotic inspection can significantly reduce commissioning time while maintaining high accuracy.
The Results: Measurable Impact for Industrial Inspection
The collaboration delivered tangible outcomes for industrial robotics applications:
- Reduced programming and commissioning time through offline programming
- Reliable transfer of simulated inspection paths to physical robots
- High inspection accuracy validated under real shopfloor conditions
- Flexible reconfiguration for diverse inspection tasks
These results confirm that AI-enabled simulation tools are not only efficient but also robust enough for industrial deployment.
A Stronger Foundation for AI Adoption
For RoboDK, working within the AI-MATTERS framework reinforced an important lesson: validating AI solutions in real manufacturing environments is crucial for industrial scalability.
Testing under operational conditions reduces implementation risk and strengthens confidence in wider adoption. The experience demonstrated how digital twin technologies, when properly integrated and verified, can accelerate the transition toward more intelligent and flexible manufacturing systems.
Looking Ahead: Expanding AI-Driven Robotics
Building on the success of this collaboration, RoboDK and ARENA2036 will continue working together within AI-MATTERS to further advance AI-enabled robotics applications.
Future activities will expand into:
- Drone-based inspection for large-scale or hard-to-reach structures
- Integration of new NEURA robotic arms, including collaborative and cognitive robots
- Automated Guided Vehicles (AGVs) for AI-enabled navigation and inspection workflows
By extending validation across emerging robotic platforms, the partnership continues to strengthen AI-MATTERS as a European reference network for testing and experimentation in AI-driven manufacturing.
Interested in exploring how AI-driven robotic inspection can accelerate your manufacturing processes? Contact our project managers for a free conversation: https://ai-matters.eu/contact