What Is A Smart Machine Tool?

What Defines a Smart Machine Tool?

The world's first CNC machine tool was a piece of mechanical equipment that combined a machine tool with a computer and control technology. However, once CNC machine tools began to be widely used in the mechanical processing industry, machine tool factories focused on the development of the machine tool's mechanical and control parameters, such as structural rigidity, spindle speed, feed speed, differential calculation accuracy, contour accuracy, etc. Software technology improved machine performance as well as productivity.

From 1990 to 2000, due to the popularization of five-axis machine tools and turning and milling machines, the functions of machine tools became more complex, and it became difficult for users to fully utilize the capacity of the machine. At this time, the machine tool industry began to pay attention to the importance of software in machine tools. Major international manufacturers began to propose the concept of the so-called “smart machine tool,” and began to develop unique software to assist users in the performance of the machine tool’s operations. Currently, smart machine tool development is still more focused on developing stand-alone functions, such as upgrading and monitoring various operational safety features and processing procedures, as well as other functions.

By 2015, almost all major machine tool manufacturers had invested a lot of resources in the development of software technology and claimed that their products were smart machine tools. However, the most important elements of smart machine tools are as follows:

1. Virtual and real integration system:
   Cyber-physical systems (CPS) establish virtual models for different aspects of manufacturing systems, and establish interactive interfaces between virtual and real physical systems. The data of the production process can be obtained from information given by sensors on the machine, the CNC controller parameters, and the user's operation history. A cloud database is constructed to store the heterogeneous data. Innovative methods are then developed for analysis of target data and the establishment of cloud-based, value-added services.
2. Internet of Things
   IoT is a network of various objects with an information sharing system between the objects. By sharing information between objects and connecting the information to a data center for background analysis, objects can be managed and controlled to achieve a smart environment. In the Internet of Things, industry can use software to directly adjust the parameters of products by analyzing huge amounts of related information and provide more complete after-sales service.
3. Big data
   

   CPS and IoT both require data exploration technology, and different processing methods will be used according to the speed of data generation, source heterogeneity, and quantity. Due to the complexity of the working environment and process requirements of machine tools, the speed and quantity of the captured data may reach a huge level. Huge data tools provide data management, distributed computing, data exploration, automatic execution, and other related modules to help users focus on solving data analysis problems and provide customers with better service quality.

   The application of signal sensing, data processing, intelligent decision-making, and action control to develop intelligent automation technology is a common application of virtual and real integration systems. Each element has a sensor and a programmable parameter interface, such as an intelligent spindle, to transmit the sensing signals of temperature, acceleration, deformation, and current during operation to the integrated platform. These sensor signals, together with the machine parameters and operation logs, are transmitted to the cloud data warehouse. The current processing responses are analyzed by intelligent APPs that compare the actual current situation to set parameters to determine if processing is abnormal, and if so, whether the abnormality can be corrected by modifying the parameters of the spindle or the controller. It can also determine when the spindle should receive maintenance, and even make a virtual comprehensive inspection of the processed product.

   The industrial upgrade 4.0 trend of the global manufacturing industry is mainly towards the development of intelligent technology, and the combining of the Internet of Things and AI to realize intelligent manufacturing. One of the main purposes of the five-plus-two plan, promoted by the government and the smart machinery industry, is to upgrade precision machinery to smart machinery. Smart machinery refers to the integration of machinery with various smart technology elements to enable them to have smart functions such as failure prediction, accuracy compensation, automatic parameter setting, and automatic scheduling. Smart Machinery provides total solutions and creates differentiated competitive advantages. Smart manufacturing refers to the introduction of smart machinery into the industry. The establishment of smart production lines requires high efficiency, high quality, and high flexibility (customization). Smart production lines joined to the Internet of Things form a manufacturing service system that provides many customized products. Precision machinery combined with smart technology, artificial intelligence, Internet of Things, big data, sensors, and smart machinery brings differentiated competitive advantages to smart production lines.

How to Upgrade Precision Machinery to Smart Machinery?

Smart machinery is combined with human experience to upgrade smart manufacturing. The current manufacturing supply trend is gradually tending towards customized orders. Small and medium-sized enterprises have limited capacity for technology upgrades. In addition, production methods and quality rely on the inheritance of experience, so upgrading to a smart production line needs to be a gradual step forward. If the manufacturing machinery and equipment are endowed with intelligence, human error and loss rate can be greatly reduced. How should manufacturing machinery and equipment be given the ability to self-test or be intelligent? The easiest way to upgrade a machine to a smart machine is to add a monitoring module to the machine and use the human experience to adjust the parameters and operating procedures. Then add some automation equipment such as robotic arms. Through the Internet of Things, you can gradually adjust and build smart production lines according to market order requirements.

1. Wisdom:
   Intelligent technology in manufacturing systems includes robots, the Internet of Things, big data, CPS, lean management, 3D printing, and sensing technology. Through the digital method, data is converted into information, and then the information is converted into appropriate actions.
2. Optimization:
   In smart manufacturing, the optimization process should include two levels. First, Experience-based processes are combined with Model-based parameters to find, verify, and transform data into the most optimal manufacturing processes. This intelligent and optimized manufacturing information will be replicated in the digital virtual environment. Through the continuous addition of on-site manufacturing data, as well as machine, market, and logistics data, artificial intelligence algorithms optimize production. New wisdom is passed back to the mechanical equipment and robots in the real environment, for real-time, optimized, smart manufacturing.

Smart manufacturing is not just adding wisdom to manufacturing. Smart manufacturing optimizes the planning and selection of product lines, manufacturing methods, supply chains, logistics chain, customers, markets, and product development. The core value of smart manufacturing comes from combining manufacturing, information, and communication technologies, introducing optimized domain know-how and smart technologies, and connecting the entire manufacturing system, from the supply chain to the outlets, to improve industrial efficiency and competitiveness of technology.