A leading company focused on the repair and remanufacturing of vehicles, mechanical components, and structural constructions. To enhance efficiency, precision, and reduce costs, the company has integrated the LE Robotic Cutting Station to automate the robotic cutting process of railway gondola side and end walls. It is characterized by its efficiency, accuracy, and cost-saving benefits, providing a longer service life, and improved performance and safety for vehicle components.
In traditional cutting and repair processes, workers manually operated cutting equipment, leading to inefficiencies, poor cutting accuracy, and high costs. Large vehicles or structures required multiple workers to collaborate, resulting in a high workload and challenging working conditions. Improving the automation level and precision of the cutting process became a critical issue for the enterprise.
LE Robotics Cutting Workstation employed advanced plasma cutting equipment, robot control technology, 3D vision, and computer control technology to achieve highly automated and intelligent cutting processes.
Workstation Components:
The workstation includes five automatic plasma cutting devices, a central control system, and a rail-mounted platform for movement. The central control system coordinates and controls the entire workstation, including the movements of cutting devices and robots. The robot system executes commands from the central control system, accurately completing cutting trajectories.
Key Features:
High cutting precision, large working range, and advanced technology.
Vehicle positioning accuracy: ±30mm, maximum vehicle movement range: 6m, maximum targeted cutting area: 2000mm × 2000mm.
Fully automatic operation, with the entire vehicle cutting process completed in less than 45 minutes.
The introduction of the automated cutting workstation achieved the following:
Innovation in the industry by applying robotized processes to achieve automated cutting processes for freight carriages. This significantly improved technological equipment and production management levels.
The application of machine vision technology opened up new ways to enhance traditional processes, laying the foundation for comprehensive implementation of robot maintenance processes.
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