Additive Manufacturing:
Automation, Digitization, Intelligence, Cloudification
In addition to its excellent hardware, Raycham's selective laser melting equipment is equipped with a powerful control management system.
The equipment host adopts an electrical system based on servo control principles, enabling sequential and synchronized control of servo axis movements.
A multi-point displacement monitoring and feedback system is implemented to achieve closed-loop control of the host's motion axis system, continuously consolidating the equipment's processing accuracy.
The independently developed shaping software can directly read print data packages generated by various commercial software. Together with optimized laser forming process data, it completes the processing and enables the automatic operation of the selective laser melting equipment.
The software system can display key parameters of the forming process in real time, and generate and update process record files during operation, achieving process supervision and result traceability to meet the needs of large-scale and industrialized processing.
Raycham's self-developed Argus system provides functions such as powder spreading quality monitoring and remote video monitoring, effectively supporting the metal additive manufacturing process in achieving intelligent factory-level quality control through "intelligent recognition, preset processing, remote control, and human-assisted" mode.
Raycham has also developed an MES system to promote intelligent management of metal additive manufacturing factories, enabling industrialized processing capabilities of clustered equipment based on hardware conditions and processing service requirements.
The MES system can centrally supply gas, electricity, and powder to a large number of equipment, realizing energy efficiency and energy consumption reduction.
At the same time, through real-time collection of equipment operating information, the MES system can manage print processing tasks, allocate human-operated processes, and schedule equipment processing plans in a unified manner, forming a rational and efficient task management process.
The software has a high degree of automation and provides efficient parsing and preview of path files, import of process parameter packages, real-time control of equipment functional modules, equipment status monitoring and alarm prompts, printing log recording, printing layer image acquisition and storage, powder quality monitoring during deposition (optional), and 3D visualization of printing progress (optional), enabling 24-hour unattended automatic printing of the equipment.
The software uses deep learning methods to monitor the powder quality during each layer of the printing process in real time. It can detect and determine defects such as “insufficient powder deposition”, “scraper stripes”, and “excessive layer height” in real time and issue alarms.
The system can comprehensively compare the hardware conditions of the equipment with the processing service requirements, and optimize the industrial processing capacity of the clustered equipment. The system enables centralized gas supply, power supply, and powder supply for multiple devices, achieving energy efficiency and consumption reduction. By collecting real-time operation information of the equipment and analyzing big data, it can centrally manage printing processing tasks, allocate manual operation processes, and schedule equipment processing plans, achieving a rational and efficient task management process.
The software has a high degree of intelligence and is equipped with a self-developed industrial Internet-specific efficient time series database system. It can continuously record parameters and videos of the printing process of multiple sets/types of powder deposition equipment for 24 hours, and can be accessed remotely within the local area network to view real-time equipment status and trace historical data.
