Xinshida Robot’s Application of Laser Cutting in the Machine Tool Industry
2025-07-16
Xinshida Robot’s Application of Laser Cutting in the Machine Tool Industry
Project Background
The global market for robotic laser cutting is projected to grow from US$5.577 billion in 2023 to US$15.539 billion by 2032, with a compound annual growth rate (CAGR) of 11.95%. This growth is primarily driven by the surging demand for high-precision and high-efficiency cutting in industries such as automotive, aerospace, and electronics. Although laser cutting equipment requires a relatively high initial investment—roughly two to five times that of plasma equipment—the long-term operating costs are lower. For instance, when cutting metals with thicknesses below 12 mm, laser cutting consumes only one-third the energy of plasma cutting and does not require frequent replacement of wear-and-tear parts, enabling the return-on-investment (ROI) period to be shortened to less than two years. Moreover, supportive government policies, such as the "Opinions on Promoting High-Quality Development of the Laser Industry," explicitly state that by 2026, laser cutting equipment should achieve large-scale substitution of traditional processes, and the first set of equipment will receive subsidies of up to 10 million yuan. At the national level, the "14th Five-Year Plan" for intelligent manufacturing also identifies laser cutting as a key area for development.
Customer needs
In laser cutting applications within the metal manufacturing industry, numerous technical challenges still remain, and the high technological barriers continue to be a key constraint on the industry's development.
Insufficient accuracy and stability
High-precision requirements coupled with a lack of dynamic compensation capability
Process Complexity and Efficiency Bottlenecks
The contradiction between human dependency and flexible production
System Integration and Cost Control
Domestic substitution ecosystem compatibility
Xinshida Solution
The robot controller independently developed by New Times Robot, featuring a nanometer-level interpolation algorithm and dynamic error compensation, achieves a repeat positioning accuracy of ±0.05 mm, meeting the precise cutting requirements for high-strength aluminum alloys used in aerospace applications and battery trays for new-energy vehicles—performance that significantly outperforms traditional mechanical cutting processes.
Error Modeling and Absolute Accuracy Compensation Technology
Relying on its independently developed full-parameter laser calibration software and high-precision laser trackers, Xindashida has achieved precise measurement of industrial robot link parameters, reduction ratios, joint flexibility, and other key parameters. Combined with advanced error modeling and absolute accuracy compensation technologies, it has enabled highly accurate positioning of the robot’s end-effector.
Self-learning backlash hysteresis compensation technology
Reverse hysteresis is a common phenomenon in mechanical systems and one of the key factors affecting the accuracy of robotic trajectories.
To address this issue, Xindashida has developed a self-learning compensation technology for backlash hysteresis. This technology can automatically detect and compensate for errors that occur during the robot’s reverse motion, eliminating the hysteresis associated with gear back-driving and ensuring smooth and precise robot movement. At the same time, based on actual machining results, the system automatically adjusts the compensation parameters to achieve optimal compensation performance.
High-Precision Dynamic Modeling and Torque Feedforward Technology
To address trajectory accuracy errors caused by servo control, New Times has introduced a high-precision dynamic model along with advanced torque feedforward technology. This high-precision model meticulously takes into account multiple factors, including the robot’s mass distribution, joint flexibility, load variations, and friction forces. In particular, it employs a nonlinear model to accurately characterize the complex friction behavior during low-speed motion, thereby ensuring high precision and reliability of the dynamic model under various operating conditions. In terms of the servo control system, by integrating advanced control algorithms and filtering techniques, the stability and rapid response capability of the servo system have been significantly enhanced, effectively reducing mechanical resonance and end-effector positioning jitter.
Optimize structural design
Through joint static and dynamic simulations of robots, Xindashida adjusts the inertia distribution across each robot joint and continuously optimizes the structural design of the robot’s body, thereby achieving both lightweight construction and high cycle rates. Based on a parameter-design approach that incorporates multiple constraints—such as constraints on robot joint torques and lifetime constraints for key components—Xindashida has significantly enhanced the robot’s mechanical rigidity and service life, laying a solid foundation for the robot to perform highly precise operations.
* After simulation calculations, the peak stress in the improved casting is approximately 40% of the peak stress in the original casting.
Industry Process Package + Independent CAM Path Simulation
The user-friendly, quick graphic insertion commands enable the system to integrate AI-powered visual recognition capabilities—such as seam detection and adaptive positioning of sheet materials—as well as a process database. Through the CAM functionality of simulation software, the system can automatically identify material thickness and optimize cutting paths, reducing manual programming time by 30%.
Associated products
SA10/2000H Welding Robot
SA6/1440H Welding Robot
SA6/1400 welding robot
