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From Industry 4.0 to Smart Manufacturing Smart Factory Faces New Technology Challenges

Mar 05, 2019

The McKinsey Global Institute predicts that the economic impact of smart factories will reach $1.2 trillion to $3.7 trillion annually by 2025. Accenture and Frontier Economics estimated the cumulative GDP impact of smart factories and industrial IoT on China's 12 industries. With the help of current policies and investment trends in China, in the next 15 years, only the manufacturing industry, smart factories and industrial IoT can generate cumulative GDP growth of 196 billion US dollars; if the impact of the Internet of Things is further expanded, various industries will Create greater value. In the case of manufacturing, for example, the economic value created by the Internet of Things will jump from $196 billion to $736 billion, an increase of 276%.

    The McKinsey Global Institute predicts that the economic impact of smart factories will reach $1.2 trillion to $3.7 trillion annually by 2025. Accenture and Frontier Economics estimated the cumulative GDP impact of smart factories and industrial IoT on China's 12 industries. With the help of current policies and investment trends in China, in the next 15 years, only the manufacturing industry, smart factories and industrial IoT can generate cumulative GDP growth of 196 billion US dollars; if the impact of the Internet of Things is further expanded, various industries will Create greater value. In the case of manufacturing, for example, the economic value created by the Internet of Things will jump from $196 billion to $736 billion, an increase of 276%.

    Technological innovation and new challenges

    Smart Factory represents a highly interconnected and intelligent digital age, and the intelligence of the factory is reflected in five key areas of connectivity, digital, big data, smart equipment and intelligent supply chain. Typical smart factories include: production equipment interconnection, item identification and positioning, automatic energy consumption detection, equipment condition monitoring, product remote operation and maintenance, parts product traceability, production performance assessment and factory environmental monitoring and other existing practical application

    At present, smart factories have several obvious technological innovations compared to traditional industrial manufacturing. Intelligent Perceptual Control: Collecting industrial data anytime and anywhere by using IntelliSense technology; Comprehensive interconnection: Through the various communication technology standards, the collected data can be accurately transmitted in real time; Deep data application: using cloud computing, Big data and other related technologies, modeling, analyzing and optimizing data to achieve full exploitation and utilization of massive data; innovative service model: using information management, intelligent terminals and platforms to achieve traditional industrial intelligent transformation and upgrading Industrial value, optimizing service resources and stimulating industrial innovation.

    Based on these technological innovations, smart factories will face six major technological development trends, namely, terminal intelligence, connectivity ubiquity, computing marginalization, network flattening, service platformization and security enhancement. The resulting management changes include increasingly diversified equipment connections, data processing to the edge of the edge, and corporate strategy from industrial individuals to ecosystems. Business operations are transferred from equipment and assets to products and customers.

    The transformation of technology and trends has brought new challenges, such as the lack of unified technical standards, industry standardization needs to be strengthened; another example, the low degree of industrialization of Chinese enterprises is generally low, the application promotion needs to be accelerated, and the development of enterprises is uneven, and the success model is difficult. Copy and so on.

    The special data ownership is pending, and data security issues need to be resolved. Therefore, from the national and enterprise level, in the face of these challenges, the overall industrial IoT layout standardization tasks need to be implemented in phases, and basic technical issues such as network interconnection and data heterogeneous integration need to be resolved, including standardization of standardized resource data. , build a good application innovation ecological environment. In addition, we must build a secure environment for industrial IoT to prevent and control security issues.

    Facing problems and technical realization

    As an inevitable trend of future industrial development, in the face of many technical challenges, smart factories need to solve many problems. Smart factories are the first to solve the problem of intelligent sensing control, to obtain the most critical industrial data by collecting industrial data anytime and anywhere. In terms of technology implementation, practical problems can be solved through various sensing control technologies, which involve technologies including sensors, device identification, and industrial control.

    The second problem that needs to be solved is comprehensive interoperability. How to transmit the collected data in real time and accurately, and ensure the security and reliability of signal transmission and compatibility with different devices are very important technical challenges. Technologies needed to address this problem include technologies such as industrial Ethernet, short-range wireless communications, and low-power industrial wide-area networks and related solutions. With data acquisition and data transmission, the intelligent core of smart factories comes from the deep application of data. Using cloud computing, big data and other related technologies, the data is modeled, analyzed and optimized to achieve full exploitation and utilization of massive data. In addition to the well-known algorithms and device services such as cloud computing, data processing technologies involved in this aspect include data cleaning, data analysis, data modeling, and data storage.

   Finally, the most special challenge facing smart factories will be the innovation of service models, integrating technologies such as information management, intelligent terminals and platforms to realize the intelligent transformation of traditional industries. This aspect involves many service model innovations beyond technology, and the most special one is security management technology, especially encryption authentication, firewall and intrusion detection technology to ensure the comprehensive security of smart factories. By connecting to the network, customers can monitor the machine's operating status, exchange data, change production instructions, and rewrite MCU stored procedures internally and externally to update device settings. This requires system manufacturers to provide an integrated solution that is safer, more reliable, and more user-friendly and reprogrammable.

    Along with the wave of the fourth industrial revolution, a new generation of information technology will have a profound impact on traditional manufacturing. From the "Industry 4.0" advocated by Germany to intelligent manufacturing and the latest industrial Internet of Things, the transformation and upgrading of manufacturing has become an irreversible trend. Rising labor costs and rising raw material prices have forced factories to adopt more efficient automation solutions. On the other hand, in the face of growing consumer demand for individuality, factories need to establish mechanisms to respond quickly to diversified needs. The establishment of a smart factory is a huge systematic project, and the vast number of developers will be important creators involved in the development of a part of this huge system engineering.