Written by Miro Adzan and Thomas Leyrer Today's terminal equipment market requires shorter product life cycles, more individual configuration products, and rapid adaptation to changing consumer rights. In the manufacturing plant, key parameters include lower resource utilization, especially lower power, faster manufacturing time and lower production downtime. These requirements require a more complex, smarter plant that leverages the cloud and uses remote big data analytics to optimize and adapt to manufacturing processes, enhancing the ability to track products throughout their lifecycle. The connection of the machine and production unit to the Internet enables a real-time view of the process data. The machine-to-product link also provides a real-time view of the product data. Raw materials and production components are processed by automated machines and production units operated by industrial service robots. Product and machine quality checks are performed during the production process to further reduce cycle times. This approach reduces human-computer interaction and focuses on higher-value tasks in the production process. Innovation breakthroughs make Industry 4.0 a reality. Many of the most significant technologies are implemented by engineering companies like Texas Instruments. For TI, addressing subsystem design challenges is critical, which will increase intelligent manufacturing design, including efficiency and flexibility, while providing real-time views, connectivity, and communication of manufacturing processes. Here are some of the key technologies for Industry 4.0 that lead to smarter, more efficient manufacturing: Compatible industrial communications. In order to obtain a transparent view of the complete manufacturing system, all data must be provided through industrial communication technologies with a common format. You may have heard the phrase "IT connects to OT." This means that the information technology (IT) world uses Internet Protocol (IP) and higher layer protocols to achieve secure Web access. The Operational Technology (OT) world uses dedicated fieldbus and industrial Ethernet, which typically only use the Ethernet standard instead of the software-based network stack component. This incompatibility between the field level and the enterprise level requires that the compatibility layer be defined as part of the Industry 4.0 framework. Connecting the Open Platform Communications Unified Architecture (OPC UA) to higher layers and connecting the fieldbus to lower-level Industrial 4.0 gateways is a short-term solution to compatibility issues. Extending communication to the product level requires low power communication. Radio Frequency Identification (RFID) is a key technology for obtaining product and machine communications. When the sensor is deployed near the product and at the machine, the power is passed through the cable. IO-Link establishes standards for the expansion of basic on/off state communication through two-way digital communication. The IO-Link gateway communicates directly with the OPC UA using Industrial Ethernet or wireless LAN. For manual operator checks, the Bluetooth® low energy connection sends data to the mobile terminal. High precision sensing. The efficiency of the production process is highly dependent on industrial sensing technology. Small batches of machine setup time have become more important. Although an online collision avoidance system is still required, collision avoidance can be performed between tools, workpieces, and fixtures for off-line simulation. Many materials and tools require water cooling, which makes it difficult for optical sensors to detect collisions. Scanners that work in dusty and humid environments are a necessity. Machine tools can fail during their service life and production quality can be degraded. Continuous force sensing of the machine tool can indicate machine breakage at an early stage. Machine quality affects the temperature sensor and acoustic sensor data. Predictive maintenance is a tidal term that describes the concept of early detection of a machine break in the early stages without affecting the production process or production quality. The multi-axis control of the machine uses closed-loop motion to position the router or material. Dimensions and surface tolerances have additional variance from the mechanical variance of the shaft, machine tool and fixture. Accurate distance measurement using linear encoders and laser distance sensors for machine calibration, motion control and quality monitoring. The manufacturing process depends on environmental data such as temperature and humidity. Active cooling and cleaning systems have an impact on environmental conditions. Flow sensors for liquids and air provide input to the machine's environmental system. Motor drive and control efficiency. A motor is a component that requires most of the energy in a production system. Variable frequency drives with closed-loop current, speed and position control enable dynamic torque curves that have a direct impact on power consumption. High precision current measurements of isolation and rotor position measurements by absolute encoders provide control algorithms for each control cycle. In addition to efficient motor control algorithms, power stage efficiency is a key factor in power consumption. The faster switching frequency of gallium nitride (GaN) transistors reduces the power of the motor drive system in the production unit. Modern production units have four main subsystems that work together: a computer numerical control (CNC) system that defines the entire production process, a motion control subsystem that drives the production motor and actuators, and other sensing and control applications. Programming logic control (PLC) systems, as well as service robots for material handling. Embedded processing. Improving the efficiency and flexibility of production systems is reflected in many aspects. Industrial communications, industrial sensing and industrial control form the basis of smart factories. Local intelligence runs on embedded microcontrollers and microprocessors. The resulting product and process data is sent to the industrial cloud for big data analytics via wireless and wireline industrial communications. Industry 4.0 Demo Wall Ceiling Motion Sensor,Ceiling Occupancy Sensor,Ceiling Pir Sensor,Ceiling Mount Motion Sensor Ningbo Multitasking Electronic Co.,Ltd , https://www.smartmultesic.com