Current status and development trend of intelligent technology application of metal cutting machine tools

**Abstract** Metal cutting machine tools are essential components of modern manufacturing systems. Their production volume and technological level reflect a country's industrial capability and competitive edge to a significant extent. China’s manufacturing industry is undergoing a historic transformation from being a major manufacturing nation to a high-level, technology-driven one. This industrial upgrade will inevitably drive the metal cutting sector to shift from low-end to high-end manufacturing. However, challenges such as low productivity, rising labor costs, and limited machining capabilities have become major bottlenecks that hinder this progress. Intelligent metal cutting technologies, including unmanned machining, high-efficiency production, and process integration, offer promising solutions. These innovations help balance efficiency, cost, and quality, while also paving the way for new development models and directions in the field. **Definition of Intelligent Metal Cutting Technology** Since the 1950s, mechanical manufacturing has evolved through several key stages: direct numerical control (DNC) for automated machining, flexible manufacturing systems (FMS) for real-time scheduling, computer-integrated manufacturing systems (CIMS) for CAD/CAM integration, and finally, intelligent manufacturing systems (IMS) and intelligent manufacturing technologies (IMT), which are currently gaining widespread attention. IMS/IMT focuses on the formalization of manufacturing knowledge, addressing uncertainty and incomplete information, and enhancing system flexibility and autonomy through smart methods. While DNC and FMS primarily replace human physical labor, CIMS emphasizes the integration of logistics and data flow, whereas IMS/IMT places more emphasis on self-organization, self-learning, and self-adaptation [1-3]. As a fusion of advanced manufacturing and digital technologies, intelligent manufacturing applies computational models, simulation tools, and scientific experiments to quantitatively describe and analyze manufacturing equipment, processes, and systems. It enables the quantitative calculation, simulation, and control of complex physical and information processes, revealing the underlying laws of manufacturing activities throughout a product’s lifecycle. This improves the adaptability and autonomy of manufacturing systems, enabling predictive and effective control of processes and performance. It also enhances system maintainability and the reusability of manufacturing information, driving the transition from empirical trial-and-error models to fully digital computing and reasoning-based approaches, thus achieving science-driven, high-performance manufacturing [4]. **Intelligent Technology for Metal Cutting Machine Tools** Currently, there is no universally accepted definition of intelligent machine tools. According to the U.S. SMPI program, they possess five core characteristics: (1) awareness of their own processing capabilities and working conditions; (2) ability to automatically monitor and optimize operational status; (3) capability to measure and assess product quality; (4) self-learning and self-adaptive abilities; and (5) inter-machine communication. Compared to traditional CNC machines, intelligent metal cutting tools not only perform standard machining but also incorporate functions like perception, reasoning, decision-making, and learning. These features manifest in several key areas. **1. Process Integration and Modular Processing** Process integration, also known as composite or complete machining, allows all necessary operations to be performed on a single machine. For example, the INDEX turning-milling compound center can handle multiple tasks like turning, milling, drilling, hobbing, and grinding, enabling full processing of complex parts. This simplifies production management, increases transparency, and reduces the need for complex planning systems. The more intricate the part, the greater the advantage over traditional dispersed processes [5]. Modular manufacturing involves deploying different processing modules and integrating them into flexible systems. Companies like Modig have developed flexible systems that allow easy configuration in series or parallel, combined with logistics and robotic loading, forming highly efficient automatic lines or unmanned workshops. German company DS-Technologie has also innovatively used reconfigurable power heads to develop high-efficiency machining centers suitable for aerospace applications. **2. Monitoring and Decision-Making Autonomy** Intelligent machine tools require self-optimization, self-monitoring, and pre-maintenance. Sensors and video systems can monitor forces, vibrations, noise, temperature, and surface quality in real time, allowing automatic optimization and error compensation based on predefined parameter libraries [7]. Maintenance can be scheduled according to the machine's condition, ensuring quality and reducing downtime. For instance, Mikron HSM series machines use vibration sensors to detect spindle health, displaying it as "g load" values. Similarly, ITC thermal compensation systems adjust tool tip positions based on temperature changes to prevent Z-axis drift. Fischer has introduced electric spindles with axial displacement compensation to improve accuracy. Modern CNC systems like Siemens’ SINUMERIK and GE Fanuc’s Proficy MTE provide detailed monitoring and predictive maintenance, enhancing overall efficiency [8-9]. **3. Information and Networking** Modern manufacturing plants require intelligent machine tools to support two-way, high-speed network communication. This ensures seamless data flow between shop floors and upper management, maximizing the use of machine capabilities. Communication devices like computers, mobile phones, and cameras enable voice, graphics, and video interactions with equipment. Machines can also be connected to production schedules, reflecting real-time status and progress. Authorized operators can monitor and manage processes remotely [10]. **Development Trends in Intelligent Cutting Technology** Current intelligent technologies in metal cutting are mainly derived from digital manufacturing. They aim for intelligent closed-loop processing, where real-time feedback from sensors helps compensate for machining errors, improving accuracy and efficiency. As IoT and cloud computing mature, future intelligent machine tools will evolve toward agent-based manufacturing and open manufacturing models. **1. Agent-Based Manufacturing** With the advancement of IoT, workpieces, tools, and even machine modules can become intelligent agents. In the future, workpieces may independently determine processing flows, select fixtures, and conduct quality checks. Tools could self-recommend parameters, and machine tools could engage in multi-directional selection, leading to a bottom-up production model that boosts efficiency. **2. Open Manufacturing Mode** China’s machine tools, especially high-end ones, face underutilization despite high import levels. Open manufacturing aims to leverage social resources, reduce costs, and speed up innovation. Cloud computing can enable machines to “connect to the cloud,” promoting resource sharing and collaboration. However, challenges like knowledge cloud management and cloud visualization remain to be addressed [11]. **Conclusion** The intelligentization of metal cutting machine tools will transform enterprises into agile, customized, and collaborative manufacturers, supporting China’s transition from a large manufacturing nation to a strong one. While some technologies are already commercialized, challenges like knowledge base creation, multidisciplinary data fusion, and standardization remain. Strengthening basic research and promoting innovation will drive the rapid development of intelligent metal cutting technologies in China. **References** [1] Zhou Ji. The digitalization of manufacturing is intelligent. China Mechanical Engineering, 2012, 23(20): 2395–2400. [2] Zhu Jianying. The meaning, technology and implementation of intelligent manufacturing. Aviation Manufacturing Engineering, 2013 (23): 30–35. [3] Li Shengyi. Intelligent manufacturing technology and intelligent manufacturing systems. Journal of National University of Defense Technology, 1995, 17(2): 1–11. [4] Department of Engineering and Materials Science, National Natural Science Foundation of China. Mechanical Engineering Discipline Development Strategy Report (2011–2020). Beijing: Science Press, 2010. [5] Zhang Wei. New trends in the development of CNC machine tools. Digital Manufacturing and Equipment, 2005 (5): 149–151. [6] Liu Guangfu, Zhang Wei. Intelligent manufacturing equipment for alliance companies. Manufacturing Technology and Machine Tools, 2001 (3): 8–10. [7] Zhang Dinghua, Luo Ming, Wu Baohai, et al. The development and application of intelligent processing technology. Aviation Manufacturing Technology, 2010 (21): 40–43. [8] Wu Baohai. The intelligent development and application of modern CNC machine tools. Aviation Manufacturing Technology, 2008 (17): 52–56. [9] Gao Binbin. Overview of the development of intelligent machine tools in the United States. National Defense Manufacturing Technology, 2009 (1): 58–60. [10] Zhang Wei. The new era of CNC: smart processing system. Aviation Manufacturing Technology, 2007 (4): 38–41. Author: Chen Chuang Wang Zengxin

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