3.2 Development Trends of Intelligent Sawing Equipments
As a starting point in equipment manufacturing, sawing involves many process parameters and derivative data from processing objects and shows obvious randomness and disorder. Sawing processing as a typical high-speed cold processing method, has several advantages in raw material consumption, energy consumption, environmental pressure, production efficiency, the heat-affected zone, etc. First, compared with traditional turning, chipping, milling, and flame cutting, the material consumption of sawing can be reduced by 70%. Second, compared with laser, flame, plasma, wire cutting, and other thermal cutting methods, the equivalent heat consumption of sawing is only 20%‒30% of the above methods. Further, sawing has no heat-affected zone, has high safety performance, and low operation and maintenance costs. Third, the sawing equipment developed based on this project has the same working precision and material consumption as laser and wire cutting, but has obvious advantages in dimension and efficiency of processing objects. The rapid development of intelligent manufacturing technology, cloud computing, 5G communications, and other digital technologies provide important support for the design of advanced sawing equipment control systems and the on-line service of sawing processing.
At present, advanced sawing equipment technologies are developing in the direction of high-speed, high-precision, high-point manufacturing, green manufacturing, functional composites, networking, and intelligent processes. Developing intelligent sawing equipments and improving the intelligence level of the sawing equipment industry has become a consistent choice for advanced sawing equipment manufacturing enterprises. In order to step into the ranks of advanced manufacturing countries and ensure the realization of the goal of increasing manufacturing power, China's advanced sawing equipments are developing steadily in four directions as follows.
(1) Characteristic optimization design of equipments and key components.
Little research has been done on machining errors caused by the vibrations of sawing, and the capacity of research in related industries is weak. The engineering applicability of high-performance sawing intelligent control systems and embedded cloud data service methods under special working conditions such as special structural workpieces, difficult to process materials, high temperatures, and high humidity environments will be limited, which also presents a barrier to next steps in this field. Due to the requirements of high stability and machining accuracy of advanced sawing equipments, higher demands are being put forward for dynamic characteristics of supporting parts and key components. While ensuring lightweight design, complete machine performance, such as dynamic and static stiffness, thermal stability, seismic resistance, working efficiency, and work stability are greatly improved.
(2) Further development of digital manufacturing and intelligent control technology.
For sawing sub-fields (hard-to-cut materials, titanium alloys, non-ferrous metals, carbon fibers), it is necessary to build a highly perfected online service platform for sawing cloud data, rationally allocate production resources, and develop functional modules, such as status monitoring, fault diagnosis, forecast and warning, process optimization, and quality control, so as to improve industrial production efficiency. Creating an intelligent sawing plant with agile service requires close collaboration and on-demand reconstruction and maximized sharing of production and information resources. In the sawing process, the factory collects and transmits data in real time. The platform carries out analyses and decisions based on collected environmental parameters and processing data, so as to achieve maximum intelligence of the whole industrial process as far as possible. Intelligent manufacturing is developing rapidly, and the competition in the global manufacturing industry led by intelligent manufacturing is intensifying. Guided by the spirit of the “Integration of Artificial Intelligence and Physical Economy”, the digital manufacturing mode of advanced sawing equipments has matured continuously. Equipment manufacturing enterprises have carried out deep digital transformations, explored intelligent solutions, and gradually moved to the top of value chain.
(3) The significance and practice of integrated manufacturing are deepened and extended.
Sawing and milling compound equipments and the new industrial trend of replacing turning-milling by sawing promote further development of sawing equipments towards higher performance and higher efficiency. It is necessary to construct an innovative ecology for intelligent sawing control, coordinate with domestic sawing enterprises and their users to share processing data, promote the establishment of sawing technology databases, and improve the training of service decision algorithms. In actual working conditions, the sawing process is affected by a multi-physical field, multi-scale, and other factors. At present, most enterprise modeling only considers the single physical field, but little modeling considers the influence of the flow field, temperature field, sound field, and other factors. In enterprise processing, relevant adjustment work is only carried out for fixed-point machines, and the above factors have little effect on the processing accuracy of enterprises. However, cloud data service faces different production environments for distributed manufacturing enterprises, and so it is necessary to consider the theoretical modeling of multi-physical fields.
(4) Promoting the construction and improvement of sawing cloud services.
Big data is the basis of cloud data services. In current sawing processing systems, the amount of data that can be used for training calculations is small, and the data acquisition capabilities of enterprises are insufficient, which brings obstacles to precision sawing based on cloud data services. For sawing subdivisions (hard-to-process materials, titanium alloys, non-ferrous metals, carbon fibers), in view of special environmental conditions such as high temperature and humidity, it is key to improve the online service platform for processing cloud data of advanced sawing equipments, rationalize the distribution of production data, and thus significantly improve industrial production efficiency. Besides, due to the simple encryption mechanism of the industrial sensor itself, the industrial Internet requires tighter technological security protection. To address the above this project will improve the encryption mechanism of the service platform, distribute and store enterprise core data, and coordinate the new man-machine relationship under cloud service processing.