2KW fiber laser cutting machine

When Laser Cutting Machine technology is combined with AI (Artificial Intelligence), intelligent path optimization and automatic material arrangement systems can significantly enhance material utilization and achieve the goal of reducing waste by 15% or even more. The core principle lies in that AI, through algorithmic models, replaces and surpasses the inefficient and rigid parts of traditional human experience.   After optimizing the layout, the walking path of the cutting head is another key point for efficiency. AI path planning is like planning the "optimal traffic route" for the cutting head. Shortest path and idle travel optimization: AI algorithms (such as the traveling salesman problem algorithm) calculate the shortest idle travel path for the cutting head to move between different part contours, reducing unnecessary "idle runs" and directly saving time and energy consumption. Intelligent decision-making on cutting sequence: AI takes into account the impact of thermal deformation and automatically arranges the cutting sequence (such as cutting the inner hole first and then the outer shape, using a skip sequence) to prevent local overheating from causing deformation of the sheet, thereby reducing the scrap rate generated as a result. Adaptive parameter adjustment: By integrating iot sensors, AI can monitor the cutting status in real time (such as changes in sheet thickness and lens contamination), and dynamically adjust parameters like power, speed, and air pressure to ensure stable cutting quality and reduce scrap caused by improper processes.   (System Integration and Value Closed Loop: From "Single-point Intelligence" to "Global Intelligence" The true value lies in the deep integration of the system with the enterprise's production process: Integration with MES/ERP: The system directly receives production orders, automatically extracts part drawings, quantities and priorities, and realizes unmanned order-to-production scheduling. Real-time monitoring and feedback: Cutting process data (such as actual utilization rate and cutting time) is collected and fed back to the AI model, enabling it to continuously self-learn and optimize. The layout plan becomes better and better as it is used. Value quantification: Reducing waste by 15% means: Direct material cost reduction: This is the most intuitive saving. Reduced hidden costs: Lower costs for waste disposal, storage and handling. Capacity enhancement: Better paths and less downtime for board replacement have improved the overall equipment efficiency (OEE). Green manufacturing: Meeting the requirements of sustainable development and reducing the consumption of raw materials.   Have questions about the parameters of this model? Click here to consult our chief technical engineer. Tel: +86 -18855551088 Email: Info@Accurl.com Whatsapp/Mobile: +86 -18855551088