FOCUS ON LASER
TRUMPF’ s SortMaster Vision system uses AI to sort laser-cut parts.
Automation also plays a critical role in part removal. Once cutting is complete, finished parts must be separated from the sheet skeleton and prepared for downstream processes such as bending or welding. Increasingly, this task is performed using robotic sorting systems.
Industrial robots equipped with specialised grippers can automatically remove finished parts from the sheet. These grippers may use vacuum suction systems for lightweight parts or magnetic lifting tools for thicker steel components. Mechanical grippers are sometimes used for complex geometries where additional control is required.
Many robotic systems incorporate vision technology to assist with part identification. Cameras positioned above the cutting area capture images of the sheet after cutting is complete. Software analyses the image and determines the position of each part within the nest. The robot then calculates an optimal picking sequence to remove components efficiently.
Automation systems also enable lightsout manufacturing. With automated loading, cutting and part removal, machines can operate unattended for extended periods, including overnight production shifts. This significantly increases machine utilisation and helps manufacturers to maximize the return on their equipment investment.
Automation challenges and real-world limitations
While automation offers significant productivity advantages, its effectiveness often depends upon factors beyond the laser machine itself. One of the most common challenges in automated laser cells involves part separation.
Small parts can sometimes remain attached to the sheet skeleton or tilt slightly after cutting. Even minor movement can create difficulties for robotic picking systems, which rely on consistent part positioning to grip components accurately.
For this reason, many cutting programs incorporate micro-tabs or small bridges that hold parts in place until they are intentionally removed. These connections maintain sheet stability during cutting and help to ensure that parts remain in predictable positions for robotic picking.
Thermal distortion can also affect automated systems, particularly when cutting thin materials. Heat buildup may cause slight warping that interferes with robotic gripping systems. In such cases, adjusting the cutting sequence or distributing cuts across the sheet can reduce thermal stress and improve automation reliability.
Intelligent nesting and smart cutting software
Software has become one of the most important elements of modern laser cutting systems. While hardware improvements increase machine capability, intelligent software determines how efficiently those capabilities are used.
Nesting software arranges parts on a sheet to maximize material utilisation while maintaining stable cutting conditions. Advanced algorithms evaluate thousands of potential layouts to determine the most efficient arrangement of parts.
Modern nesting systems take into account variables such as heat distribution, machine acceleration limits, part removal sequence and skeleton stability. These factors help to ensure that parts remain stable during cutting while
Image: TRUMPF. minimizing overall cycle time. Artificial intelligence( AI) is beginning to enhance these systems. AI-assisted nesting software can analyse historical production data and recommend parameter adjustments based upon previous results.
Post-processor software converts nesting programs into machine-specific instructions that control cutting speed, piercing cycles, assist gas selection and motion control parameters. These programs also coordinate communication between the laser cutting machine and any connected automation systems.
When robotic sorting systems are used, the nesting software generates a digital map of part locations within the sheet layout. This information is transmitted to the robot controller so that the robot knows exactly where each component is located.
Maximizing productivity
When evaluating laser cutting productivity, it is easy to focus solely on cutting speed. However, the total production cycle for a sheet includes several additional operations such as loading material, piercing the sheet, repositioning the cutting head, exchanging pallets and removing finished parts.
In many production environments, these non-cutting activities represent a significant portion of total cycle time. As a result, improving overall productivity often depends more upon reducing idle time than on increasing laser power.
Automation systems, intelligent nesting software and optimised cutting strategies work together to minimize these delays. By reducing non-cutting time and stabilising the cutting process, modern laser cutting systems can achieve substantial productivity improvements without relying solely on higher power levels.
The future of laser cutting
Laser cutting technology continues to evolve as manufacturers develop more advanced laser sources, intelligent beam control systems and fully integrated automation solutions. Beam shaping technologies, robotic material handling and AI-assisted software are transforming laser cutting machines into highly intelligent manufacturing systems.
For fabricators, understanding how these technologies interact is essential for maximizing equipment performance. When advanced laser sources, automation systems and intelligent software are combined effectively, modern laser cutting operations can achieve new levels of productivity, reliability and manufacturing precision. n
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38 | ismr. net | ISMR March 2026