Driving Efficiency and Quality
Why Manufacturers Choose SmartRay’s AI‑Driven Weld Inspection
Automotive manufacturers are under more pressure than ever to increase quality, reduce waste, and speed up production, all while managing labor shortages and rising energy costs. SmartRay, a leader in high‑precision 3D inspection technology, delivers tangible solutions to these challenges with its AI‑powered weld inspection system JOSY. Unlike many Industry 4.0 concepts that remain theoretical, SmartRay offers real, deployable AI applications that are already transforming production processes today.

A Practical Path to Industry 4.0 — From CAD to Inspection
SmartRay’s innovation is rooted in its holistic workflow. It begins with customer CAD data, which is utilized to automatically generate robot inspection paths, followed by a validation process through digital simulation. Subsequently, the JOSY system is employed for inline AI inspection, complemented by a statistical analysis of weld quality. Ultimately, this process facilitates future closed-loop adjustments in actual production settings.

Tool path generation from CAD

Robot-Simulation

Weld inspection with MICO-sensor
Presented recently at EY’s European Industrial AI Innovation Hub, this workflow demonstrates a complete digital thread extending from product design to automated process optimization. Visitors saw how SmartRay’s system reduces manual programming, eliminates errors, and delivers 100% inspection accuracy. The integration of AI technology ensures continuous improvement and adaptability in dynamic industrial environments.
Why Customers Choose JOSY: Clear, Measurable Benefits
1. Up to 80% faster setup and commissioning
JOSY’s new AI algorithms detect weld borders instantly – without manual parameterization or on‑site training. This reduces integration time by up to 80%, allowing manufacturers to start optimizing processes from the very first part produced.
2. Early availability of critical quality data
SmartRay delivers quality insights before mass production begins – a major advantage during vehicle launch phases, where weeks gained can translate into millions saved.
3. Lower maintenance and greater process stability
Welding conditions continuously change in real production. Traditional systems require frequent re‑adjustment. JOSY does not. Its AI adapts automatically to variation, maintaining stable inspection performance with minimal operator input.
4. Higher quality, fewer defects, and reduced waste
JOSY’s statistical analysis tools not only detect out-of-spec welds, but also identify recurring process issues and their root causes, helping prevent defects instead of repairing them later.

Set up Time for Key Process Criteria Inspection

Installation Process of a Production Facility

Variations in the Automated Welding Process Over Time
The JOSY Advantage: One Partner For A Seamless Process
Many solution providers concentrate on specific aspects of the workflow, such as inspection, simulation, or analytics. SmartRay distinguishes itself by not only offering individual technologies but also by integrating these elements cohesively—from CAD and planning to inspection and process optimization. This unified, end‑to‑end approach is what truly sets SmartRay apart across the entire industry landscape.
By choosing SmartRay, customers benefit from:
- A comprehensive, integrated solution
- Proven AI that operates effectively in real-world production environments
- Easier integration and reduced maintenance
- Faster launch times
- Enhanced quality and decreased cost per part
- A future‑ready path toward closed-loop factory automation
In short: JOSY doesn’t just inspect welds – it transforms welding into a transparent, predictable, and optimizable process that consistently strengthens overall production performance.

Conclusion: A Smarter Way to Build the Cars of Tomorrow

Why choose automated weld inspection from SmartRay?

Working with you
SmartRay provides a complete turnkey solution to your weld seam inspection application from initial evaluation through to project handover:
