The integration of IT, OT, and CT drives service and data innovation
Looking back on the past, Information Technology (IT) and Operation Technology (OT) seldom overlap, but entering the Industry 4.0 era, through the Internet of Things, big data, and cloud intelligence, IT and OT can finally start a dialogue. Sensors in the OT field Obtain data, upload it to the cloud center in the IT field, perform big data analysis, and multiply various innovative applications.
Industry 4.0 opens up the integration of IT and OT. If Communication Technology (CT) is added to the scope of integration, it can be said to be a perfect interpretation.
Specifically, the core architecture of the Industrial Internet of Things and Industry 4.0 is centered on data innovation and service innovation, which means that the manufacturing industry also needs different industries like the service industry and agriculture. They are all based on meeting customer needs, and they play the role of an intermediary in the traditional value chain, such as agents, distributors or retailers, etc., which may disappear under the effect of de-intermediation in the future. By then, product manufacturers must Know how to make good use of ICT technology to directly provide services to end-users.
The integration of IT, OT, and CT drives service and data innovation
How to realize data innovation and service innovation? It must rely on the integration of IT, OT, and CT. The so-called IT includes e-Commerce, enterprise resource planning system (ERP), supply chain management system (SCM), customer relationship management system (CRM), product life cycle management system (PLM), and even office automation system (OA). All of these are projects that the IT department is relatively familiar with.
OT generally refers to technologies related to factory operations, and mainly covers three categories:
Factory information systems such as Shop Floor Control (SFC), Manufacturing Execution System (MES), and monitoring and integration control (SCADA) need to be integrated with IT systems; and in the process of connecting information technology with the physical world of the industrial field, Sensors play an important role.
It cannot be denied that OT is closely related to the sensing and control of the physical world. Therefore, if the industrial Internet of Things technology can be used to drive smart robots or smart production equipment to produce the best operating efficiency, it is indeed a core issue.
CT includes various wired communication, wireless communication, long-distance communication, and short-distance communication and other related technologies, such as Wi-Fi, Bluetooth, Zigbee, 4/5G and other wireless communication technologies, up to the industrial communication and bus technology categories, such as Siemens PROFINET, Beckhoff, EtherCAT, etc., and finally talk about the integration between different communication technologies, all need to be continuously promoted and implemented.
Under this premise, many Industry 4.0 solutions with Cyber-Physical Network Converged Production System (CPPS) as the core will not deviate from the main axis of IT, OT and CT integration in terms of architecture design. Before the integration of virtual reality and reality, as a manufacturing company, it has two distinct worlds. One is the physical world located on the manufacturing side, which contains industrial Fieldbus networks, embedded RTOS operating platforms, and I /O control module, there are projects such as Soft-LogicPAC, VC++ programs, and the other side is the virtual world, including the Internet, wireless communication, Big Data Concentrator, and Mobile HMI.
Internet of Things Gateway pierces the needle and solves the obstacles to the integration of virtual and real as soon as possible
Since it talks about the integration of virtual and real, it means that manufacturing companies must jump out of the automated control framework of the field, and further connect the factory equipment and controllers to the virtual cloud world, to upload the cloud data through the network to various large amounts of data obtained at the industrial site. Center, perform big data analysis, and thus strengthen production efficiency and improve corporate operating efficiency.
In the integration process, it is necessary to use the IoT gateway to connect the virtual and real worlds. Furthermore, this gateway must have a powerful translation function and the ability to recognize various Fieldbus communication protocols. Not only that, but also Supports Internet or cloud communication-related protocols and technologies such as MQTT, SQLite, etc., so that the effect of seeking common ground while reserving differences can be brought into play, so that manufacturing companies that establish smart factories can follow the shortest without having to spend a lot of money to update equipment, and do not need to stop production and implementation. Path to accelerate the realization of the vision of a digital factory and Industry 4.0.
Why is the integration of different Fieldbus communication protocols so important to realize the digital factory and Industry 4.0? This is because the field control systems of most factories at the present stage are only used to provide machine control functions at the beginning of the introduction, so some standard communication protocols are not used. If things go on like this, it will be difficult to integrate production machines and industrial control networks. Without the help of intermediary mechanisms such as IoT gateways to perform the translation function, the machine will continue to stay in a non-IP format, which will result in the inability to communicate and connect between the machine and the machine or between the machine and the industrial control network. It is impossible to form a group that can be coordinated and controlled, let alone support and replace each other. In the end, it is impossible to realize the digital factory and Industry 4.0 or the Industrial Internet of Things IIoT.
It is worth mentioning that in recent years, many industrial Internet of Things application cases has pointed to predictive maintenance purposes, that is, managers only need to remotely collect and upload sensor, controller and other data, supplemented by big data analysis and predictive modeling technology obtains the machine failure precursor characteristics, and assists the real-time alarm mechanism, to grasp the situation before the machine is about to fail, and deploy contingency plans in time to avoid sudden machine failures that cause the production line to stop suddenly. Cause huge losses, this application example is extremely important to manufacturers. However, once the underlying communication barriers are not resolved, it is impossible for managers to remotely monitor the status of the machine, and of course, they cannot predict the benefits of maintenance.
But what is certain is that the entire manufacturing industry, such as the production of chips, the production of panels, the assembly of 3C products, metal processing, textiles, plasticization, bicycles, machinery, automobiles, and other different manufacturing businesses, often have the maturity of factory automation. Different, so a set of integrated and applicable solutions is needed to enable all manufacturing companies to gradually upgrade to the industry 4.0 level.
Promote 3.0 first and then challenge 4.0 goals in an orderly manner
When manufacturers are determined to seek upgrading and transformation towards Industry 4.0 and the Industrial Internet of Things, they must first understand how far they are from 4.0, so that they can prescribe the right remedy and prioritize their deficiencies.
Based on the experience of observing the clients over the years, some companies first listed the projects that need to be implemented in Industry 4.0 and then reviewed the current status of most manufacturing companies one by one. In terms of the three most critical projects, for the first process automation and information management, the degree of process automation varies greatly due to industrial differences and enterprise scale. Most large enterprises have introduced ERP and MES, but Small and medium-sized enterprises are not necessarily; for the second application of robots, industries such as automobiles and semiconductors currently have a relatively high import ratio. Other industries such as 3C, plastics and rubber, food, and metal component manufacturing have great demand.
In the part of machine equipment IoT and sensor applications, high-end manufacturing has a deeper application, and the rest have great room for improvement.
Regarding other Industry 4.0 implementation projects, including flexible and optimized manufacturing capabilities, industrial big data analysis, digital design and manufacturing simulation, and digital product life cycle management, due to the different maturity levels of different companies, many industries are still stuck The low level, only falling at 2.0, must first try to advance to 3.0 before continuing to win 4.0.