1746-OW16 Siemens Yang Dahan: Digital manufacturing will open the golden decade of China's machine tool industry

After the rapid development from 2001 to 2017, in the past few years, China's CNC machine tool industry has entered a difficult cycle of declining demand and fierce competition in the industry. I see from some public data on the market that China has about 600-700 CNC machine tool factories disappearing in the market every year, and there are 500-600 machine tool companies pouring into this market every year, and no matter the nature of the enterprise, the size of the enterprise, or how brilliant history it has, none of them are in this dynamic market.

However, if the seemingly downward "basic disk" is analyzed, it is not difficult to see that the main decline in demand is simple, low-cost, low precision, simple CNC machine tools, and the demand for high-end machine tools is actually growing against the trend.

This can also well explain the two changes in the Chinese machine tool market: on the one hand, more and more Chinese local machine tool manufacturers are seeking industrial upgrading, transformation, and gradually moving towards the high-end field dominated by imported machine tool manufacturers; On the other hand, the main market of China's machine tool exports has begun to shift from developing countries to the European market, and has become the supplier of some top manufacturing enterprises in the automotive field. This shows that only those enterprises that innovate quickly and actively upgrade and transform can win the market, which has become the consensus of everyone.

Virtual debugging for machine tool innovation

Innovation in the machine tool industry has a high risk cost. In many cases, the proportion of machine tool companies developing a new model, improving it through process verification, and eventually bringing it to the market and forming large-scale applications is less than half. The lack of experimental verification ability and conditions is a common problem for traditional machine tool enterprises in China.

In fact, with the help of computers for machine tool 3D model design is already a very mature technology, but the current machine tool, especially the five-axis machine tool in the real cutting environment behavior is difficult to use computer simulation. Virtual debugging can solve the problem of manufacturability verification.

With the digital twin technology of Siemens CNC system to create a digital map for the machine tool, the user can make many structural adjustments to the machine tool on the computer, and the machine tool can also be used as a virtual machine tool for real cutting of parts after the design. Virtual debugging is not a simulation tool, it redefines a whole new approach and perspective to the design, verification and evaluation of a machine tool. I believe that in the next ten years, the digitalization of machine tool design and the digitalization of machine tool process verification, and the digitalization of the final application efficiency of machine tools will have great development and changes, which will also be a golden decade for the digital manufacturing of machine tools in the Chinese market.

Ignoring the digitalization of core processes is of limited value

The digitization of machine tool industry is usually divided into two directions, one direction is to integrate logistics information and process information into a platform through the data collection of the whole process of the production site, and then use algorithms to optimize the production process. For example, the boot information of the machine tool, the comprehensive use efficiency of the machine tool, etc., belongs to this category. The other direction is the dynamic response, that is, real-time analysis and optimization of the cutting process, to solve the problem of whether the speed, torque, cutting and turning of the tool can be improved in a period of time on a curved surface.

The significance of these two directions is easier to understand if you use the analogy of a car. The former is equivalent to the water temperature seen from the dashboard, the amount of fuel stored in the tank, the driving distance, etc., which can be collected by standard sensors for long periods of time; The latter is the moment when the accelerator is pressed down, the CPU on the engine iterates repeatedly at the speed of 1/10 millisecond, so as to obtain accurate torque and oil amount of short cycle data. For a car, the optimization of the engine is obviously more important than the modification of the instrument panel.

The core process of machine tools is cutting. Without data analysis of the core process of the machine tool, the value of the data that can be obtained is obviously very limited. Data mining for cutting process is the key to directly enhance efficiency, improve quality and improve labor productivity.

For the data of the cutting process, Siemens has developed a lot of optimization algorithms based on artificial intelligence to achieve the best arrangement of the tools in the tool library, greatly improving the system performance and significantly reducing the production time. For example, the "adaptive cutting" algorithm provided by an aerospace parts manufacturer can accumulate millisecon-level data such as the displacement of the machine tool, the speed of the tool, and the resistance of the tool during the cutting process in a database, and when the cutting is finished, the artificial intelligence algorithm is used to conduct a comprehensive analysis of these data and give further optimization suggestions. Each processing process is continuously optimized on the basis of the last one. Because there is nothing more valuable to a business than "improving productivity by 1%".