Dazu has rich experience in the field of precision cutting, and has good customer reserves in 3C, automotive, mold and other industries. It has established strategic cooperation with Siemens, a global industrial giant, and has a global service network to ensure the high-speed, high-precision and high-efficiency processing of CNC machine tools, and timely respond to the market demand for product updates. CNC machine tools are facing a variety of end users, and the demand for intelligent machine tools is getting higher and higher. Customers not only need good machining accuracy and machining speed for machine tools, but also need real-time monitoring and intelligent feedback of the machining process to avoid poor machining caused by changes in people, machines, materials, methods and links in the machining process, and to optimize the machining quality, efficiency and cost. Provide key data for plant intelligence.
The basic data source is constructed on the machine tool, and the quality of the data determines its application value. Based on the machining principle, the relevant data is obtained from the following three aspects:
Sensor data: vibration, power, temperature, pressure, flow;
CNC system data: tool number, program name, current coordinates, feed, speed; Non-electrical data: operator, work order information, tool information, etc.;
Through the analysis and modeling of the machining process data, the machine tool monitoring, tool monitoring, material monitoring, parameter monitoring and manufacturing process monitoring are transformed into a real-time control system, which can feed back the machining process in real time and optimize the machining process accordingly.
The above case is the end user site of Dazu Laser, which provides structural parts of new energy batteries for major new energy battery manufacturers around the world. The processing scenario is the deep hole processing of parts. The tool is suspended for a long time during processing, and it is easy to break when encountering abnormal conditions during processing. In addition, the quality fluctuation of tool batches and the inconsistency of processing material uniformity will aggravate the abnormal tool breakage. One operator needs to operate multiple machine tools, and it is difficult to find the broken knife in time, resulting in waste products or damage to tooling jigs and machine tools. IGTech uses spindle load data to monitor the machining process in real time. When the tool is abnormal, the load characteristic value curve will change suddenly. By finding the change of the curve in time, the tool's abnormality can be monitored. Through the real-time judgment of the monitoring software, the error of manual judgment can be avoided, the operation of one person with multiple machines can be realized, and the efficiency and safety can be improved.
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