**1. Introduction**
Metal cutting is one of the most widely used methods for shaping parts and plays a crucial role in the machinery manufacturing industry. Over the past two decades, with the continuous advancement of CNC machining technology and cutting tool development, research on high-speed cutting has deepened significantly. As a result, high-speed cutting has become increasingly prevalent across various industries such as aerospace, automotive, machine tools, and mold manufacturing.
The concept of high-speed cutting was first introduced by Dr. Carl J. Salomon from Germany in 1931. Since the 1960s, especially after the 1980s, industrialized nations have invested heavily in the development of this technology. By the 1990s, high-speed cutting had entered a more mature phase and its applications expanded further. Generally, high-speed cutting refers to a cutting speed that is five to ten times higher than conventional cutting or a spindle speed of 10,000 rpm or more. However, the exact speed range can vary depending on the workpiece material, cutting method, and tool material.
High-speed cutting is characterized by:
- High cutting speed (e.g., turning at ≥500 m/min, milling at ≥300 m/min, drilling at ≥200 m/min)
- Large feed rate (e.g., Vf = 20–50 m/min or fz = 1.0–1.5 mm per tooth)
Compared to traditional cutting, high-speed cutting can increase material removal rates by more than 3.5 times while reducing costs by 20% to 50%. It also improves machining accuracy and surface quality by 1–2 levels. This makes high-speed cutting a key focus for countries around the world. Additionally, it enables new machining approaches for difficult-to-cut materials, such as directly machining hardened workpieces to achieve "cutting-grinding" effects.
**2. Overview of Metal Cutting Database Development**
Establishing a metal cutting database and providing optimized cutting data is an effective way to enhance the efficiency and cost-effectiveness of machining processes. These databases serve as essential foundations for modern manufacturing technologies like CNC CAPP, CAD/CAM, FMS, and CIMS. The first metal cutting database was created in 1964 by the U.S. Technical Cutting Joint Research Corporation and the U.S. Air Force Materials Laboratory, known as the Air Force Processing Data Center (AFMDC).
Since the 1960s, many developed countries have established their own metal cutting databases. Notable examples include the German INFOS and the U.S. MDC (Machinability Data Center), which evolved from AFMDC. In China, research on metal cutting databases began during the "Sixth Five-Year Plan" period. Institutions such as the Chengdu Tool Research Institute, Southeast University, and Nanjing University of Aeronautics and Astronautics have developed practical databases, such as CTRN90V1.0 and NAIMDS.
**3. Core Technologies of High-Speed Cutting Databases**
A high-speed cutting database must be built on the foundation of mature cutting theory, widespread application of cutting techniques, and rich cutting parameters. With the rapid development of computer and database technologies, these systems have evolved to support advanced functions such as intelligent recommendations, optimization, and prediction.
Unlike general cutting databases, high-speed cutting databases must include features like recommended cutting tools, optimized parameters, and strong integration with CNC systems and CAD/CAM software. They should also support:
- **Communication with CNC systems**: To leverage the automation of high-speed machining.
- **Reasoning functions**: Using AI, rule-based reasoning, and fuzzy logic to generate new cutting data.
- **Distributed structure**: To support large-scale enterprises across different locations.
- **Network capabilities**: For remote access and collaboration in agile and networked manufacturing.
- **Prediction functions**: Using artificial neural networks, finite element analysis, and statistical models to predict machining outcomes like surface roughness and tool life.
**4. Basic Structure of High-Speed Cutting Database**
As shown in Figure 1, the high-speed cutting database includes input and output components. Users provide specific requirements, such as workpiece material, dimensions, and tolerances. The system then outputs tool recommendations, cutting parameters, and other relevant data.
The database structure typically follows a Client/Server (C/S) model, allowing for distributed storage, scalability, and efficient processing. It consists of several key parts:
- **Database**: Stores cutting data, tools, workpieces, machine tools, fixtures, models, and processing examples.
- **Data Sources**: Includes factory, lab, and literature data.
- **Evaluation System**: Verifies the accuracy of stored data.
- **Application System**: Supports query, update, optimization, and prediction.
- **Network Interface**: Enables remote access and data sharing.
**5. Conclusion**
The development and implementation of high-speed cutting databases are critical for the future of the manufacturing industry. These databases not only improve machining efficiency and reduce costs but also enhance product quality and market competitiveness. By integrating AI, predictive modeling, and network technologies, high-speed cutting databases will continue to drive innovation and growth in the metal cutting sector.
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