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34KW Total Power Consumption CNC Inverted Rail Welding Robot For Steel Weld
| MOQ: | 1 set |
| Price: | Negotiable |
| Standard Packaging: | Wooden case |
| Delivery Period: | 60 days |
| Payment Method: | L/C, T/T |
| Supply Capacity: | 200 sets/year |
34KW CNC inverted rail welding robot
,CNC welding robot for steel weld
,CNC angle punching machine with warranty
34KW Total Power Consumption CNC Inverted Rail Welding Robot For Steel Weld
Product Parameters:
| Category | Content | Main Technical Parameters | Remark | ||||
| Robot performance | Arm span | 2010mm | — | ||||
| Repeatability | ±0.07mm | — | |||||
| Load capacity | 12kg | — | |||||
| Visual performance | Near field of view | 461×255mm@300mm | — | ||||
| Far field of view | 1150×660mm@800mm | — | |||||
| Z-axis single-point repeatability | 0.015mm @300mm0.1mm @800mm | — | |||||
| Visual accuracy | ≤0.5mm | — | |||||
| Full frame acquisition time | 0.2-0.8s(Full frame rate Max:6FPS) | — | |||||
| Light resistance | 180000Lux | — | |||||
| Overall parameters | Power supply |
Three-phase five-wire system 3×380v±10%/50HZ |
— | ||||
| Degrees of freedom | 7-axis | 8-axis | 9-axis | — | |||
| Number of robots configured | single unit | single unit | single unit | Depends on the design | |||
| Total power consumption | 34kw | 37kw | 55kw | — | |||
| Floor area | (4m + track length) × (3 + rail spacing) × 3.5m | — | |||||
This robotic system adopts an inverted track configuration, utilizing overhead or suspended installation to achieve precise positioning control while substantially extending the effective operating range. It is suitable for processing workpieces with a maximum width of ≤3 m and a maximum height of ≤500 mm, including bridge deck components and similar structural parts.
The system can be further configured with Y- and Z-axis extensions to create a nine-axis cantilever robotic platform, providing an expanded machining envelope and greater operational flexibility. When integrated with multiple 3D vision systems, the equipment can simultaneously identify and model multiple workpieces from a single captured image, enabling efficient workpiece recognition and intelligent automated processing.
