TCI Cutting integrates AI into new laser cutting machines

TCI Cutting is driving the development of smart factories with the introduction of IA Smart Motion 2.0^®. The advanced system integrates artificial intelligence directly into the motion control of fiber laser cutting machines. Combined with the company's proprietary MAS Concept^® (Machines, Automation, and Software)—which includes the production management software Manager PRO^® and the automated palletizing system TCI Sorter 3.0^®—the Spanish manufacturer creates a networked ecosystem. This end-to-end production model aims to seamlessly connect machines, robotics, and software to maximize productivity and process autonomy beyond the mere cutting operation.

Predictive path planning and dynamic kinematics
Traditionally, laser cutting cycle times are severely impacted by abrupt braking and acceleration during complex directional changes. The new AI-supported IA Smart Motion 2.0^® control predictively analyzes the upcoming cutting path and adaptively adjusts the machine's dynamic behavior—speed and acceleration—to the actual geometry of the workpiece. When the laser head approaches curves or tight radii, the system modulates the movement early, allowing high speeds to be maintained on straight stretches, rounding and braking only where precision requires it. Deployed across TCI Cutting's 2D, 2D+Bevel, and 3D fiber laser cutting solutions, this technology ensures smoother movements, optimized contour quality, and reduced mechanical wear.

End-to-end data flow from cut to pallet
Optimizing pure cutting performance is only part of the equation; the real bottleneck in modern sheet metal manufacturing often lies in downstream intralogistics and material handling. This is where TCI Cutting's MAS Concept^® steps in: the Manager PRO^® software bundles all production data and networks shop floor planning in real time with the physical machines. After the cut, the TCI Sorter 3.0^® takes over, integrating the AI-based logic of Smart Sorting^® technology. This intelligent system autonomously decides on extraction strategies and arranges the cut parts on pallets according to priorities for subsequent manufacturing steps. Each process step feeds new data back into the overall system, drastically reducing manual interventions and continuously optimizing the material flow.

Additional Context: Moments of Inertia in Gantry Machines and Robot Gripping Logic
This section describes physical and kinematic principles of sheet metal processing not included in the original press release.

In high-performance sheet metal processing, the gantries of modern fiber lasers move with enormous accelerations, often exceeding 2 to 3 G. Under these extreme forces, the physical limits of the machine structure are reached: abrupt directional changes in sharp corners generate high-frequency vibrations and mechanical jerk, which can appear as fine chatter marks on the cutting edge. Conventional CNC controls brake the massive drives heavily before corners, costing valuable cycle time. A predictive AI control calculates the exact moments of inertia of the moving masses in advance and modulates the servo drives in fractions of a microsecond to navigate corners in smooth profiles and eliminate mechanical resonances.

Another massive challenge in "lights-out" automation (unmanned manufacturing) is the subsequent sorting of the parts. During cutting, nesting is designed to minimize sheet metal waste, resulting in entirely different geometries lying extremely close and intertwined on the cutting bed. During automated unloading, gantry robots with suction cup grippers must calculate the exact centers of gravity of these asymmetrical parts—which may be fixed by micro-joints or partially tilted—without shifting adjacent workpieces or placing the vacuum cups over holes in the part. Complex AI algorithms are deployed here to interpret the nesting plans and dynamically calculate the optimal gripping, lifting, and depositing strategy.

Edited by industrial journalist Lekshman Ramdas, with AI assistance.

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