Automatic generation of co-working paths for dual-head laser drop feeders and applications
- DOI
- 10.2991/978-94-6463-581-2_82How to use a DOI?
- Keywords
- Laser drop; Cooperative work; Safety avoidance; Automatic path generation; Hot stamping
- Abstract
The cooperative work path automatic generation technology of dual-head laser drop feeder is studied, aiming to improve the efficiency and safety of laser cutting production line. By designing key technologies such as central control system, division of cutting tasks, real-time position feedback, collision detection and avoidance, and coordination of cutting parameters, the cooperative work of two independent laser cutting heads in the same plane is realized. This technology not only optimizes the cutting path, but also ensures the safety and consistency of cutting quality during the cutting process. The experimental results show that the dual-head cooperative work significantly improves the production efficiency and provides a new solution for the application of laser drop feed production line in complex processing fields such as hot stamping.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Chen Yin AU - Yanping Yang AU - Jianye Wang AU - Chuanyong Yin AU - Zhan Wang AU - Xiang Li PY - 2024 DA - 2024/12/07 TI - Automatic generation of co-working paths for dual-head laser drop feeders and applications BT - Proceedings of the 7th International Conference on Advanced High Strength Steel and Press Hardening (ICHSU 2024) PB - Atlantis Press SP - 692 EP - 698 SN - 2590-3217 UR - https://doi.org/10.2991/978-94-6463-581-2_82 DO - 10.2991/978-94-6463-581-2_82 ID - Yin2024 ER -