The "Guiding Opinions of the State Council on Deepening the Development of the Industrial Internet by "Internet + Advanced Manufacturing"" proposes that "by 2025, 3-5 internationally competitive industrial Internet platforms will be formed." Cultivating an internationally competitive industrial Internet platform is related to the dominance of industrial operating systems in the next 10-15 years. It is related to the establishment, consolidation and strengthening of a country's manufacturing competitive advantage. It is time-consuming and arduous to build a local industrial Internet platform. The mission is great. From the supply side point of view, China's industrial Internet platform faces four "card neck" bottlenecks in industrial data collection, big data modeling analysis, industry mechanism model precipitation, industrial APP cultivation, etc., and it is urgent to make breakthroughs as soon as possible.
Data collection is the foundation of the industrial Internet platform. The first problem to be solved by the industrial Internet platform is to connect people, machines and business systems in the industry, but it is not an easy task to connect equipment to the industrial site. At present, in China's industrial enterprises above designated size, more than 80% of the machines and equipment are “dumb†devices that are not connected to the Internet and cannot talk. Only 20% of the devices are connected to the network and can talk, but these devices follow different communication protocols. There are serious "language barriers" that have become the bottle neck bottleneck restricting the construction of industrial Internet platforms.
On the one hand, 80% of the devices are not connected to the Internet, and the level of digitization of the devices is low. The overall level of China's manufacturing industry is in the transitional phase from 2.0 to 3.0. There are many old equipments and low digitization levels. In 2017, the digitalization rate of production equipment of industrial enterprises above designated size in China was 44.8%, and the networking rate of digital equipment was 39.0%. The way to achieve equipment networking has made the industrial Internet platform difficult to collect data, high cost and low efficiency.
On the other hand, 20% of the devices are networked, but the communication protocols are not uniform. In the past 30 years, various automation manufacturers, research institutes and standardization organizations around the world have launched hundreds of fieldbus protocols, industrial Ethernet protocols and wireless protocols around equipment networking. The protocol standards are numerous and relatively closed, and industrial equipment interconnection is difficult. Restricting the cloud on the device, it is imperative to build a technical product system that is compatible and converts multiple protocols.
Industrial equipment networking is not an end, the purpose is to establish a digital image of industrial equipment in cyberspace, using industrial big data and artificial intelligence to "train" industrial APP to solve the actual business pain points. The essence of the industrial Internet platform is to model and analyze the data generated by machine equipment and business systems, and transform the data into application services that guide equipment and business optimization. At present, limited by the data collection bottleneck and the professional, relevance, process, timing and analytic characteristics of industrial big data itself, industrial big data modeling and analysis requires platform enterprises to have both industrial genes and big data genes, resulting in The existing industrial Internet platform industrial big data modeling and analysis capabilities are relatively weak.
First, the data types are incomplete, which restricts industrial big data modeling analysis and industrial APP functions. Compared with Internet big data, focusing on the “quantity†and “correlation†of data, industrial big data pays more attention to the “full†and “associativity†of data to ensure that comprehensive information about the true state of industrial equipment can be extracted from the data. Limited by the data collection capability of the device and the incomplete data source, this will restrict the industrial big data modeling analysis and the development of the industrial APP to a certain extent. Currently, there are many industrial APPs based on a single data source, based on equipment and business systems. There are few industrial apps for multi-source heterogeneous data development.
Second, the data quality is not high, which restricts industrial big data modeling analysis and industrial APP performance. Industrial big data tends to be missing, scattered, and intermittent. Low-quality data will directly lead to the inability to use modeling analysis results or more serious consequences. Data quality needs to be pre-judgmented and modified, so data is “cleanedâ€. Work will even account for about 70% of industrial APP development time. Based on the data quality problem, there are more industrial monitoring and fault diagnosis industrial APPs on the current industrial Internet platform, and there are fewer industrial warning APPs for forecasting and early warning, especially for intelligent decision-making.
The industry mechanism model is the core of industrial PaaS and is a concentrated expression of platform technology capabilities. The industry mechanism model is to make explicit, modeled and coded the whole process of industrial R&D design, manufacturing, management and other manufacturing processes through software technology. Each industry mechanism model is a building block module for industrial use. APP developers are flexible in calling to promote the precipitation, dissemination, reuse and value creation of industrial knowledge. The prominent problems facing the current industrial Internet platform are the lack of development tools and the lack of industry mechanism models, which are far from fully meeting the needs of industrial applications.
First, China's industrial software is backward, it is difficult to quickly transfer offline capabilities into an online model. China's manufacturing industry accounts for 20% of the world's manufacturing industry, but China's industrial software market share only accounts for 1.7% of the world's industrial software market share, while more than 90% of China's industrial software imports, which fully demonstrates China's industrial technology. The level of softwareization and accumulation is far from enough. It lacks the offline strength to model and code the industry mechanism in a short period of time.
Second, China's industrial sector is complex, and it takes time to establish a complete system model library. China has 39 industrial categories, 191 medium-sized, and 525 sub-categories. It is the only country in the world that has all the industrial categories in the UN industry classification. Each industry has its own unique industry knowledge, and the industry of each industry. The basic principles, key basic materials, core basic components (components), advanced basic processes, and industrial technology infrastructure are encapsulated into a digital model, which is a systematic project that requires the joint efforts of the government and the whole society.
Industrial APP is the key to the industrial Internet platform. However, the development of the industrial Internet platform is still in the primary development stage. The industrial PaaS platform is not enough. The so-called industrial APP on the industrial Internet platform is basically the “immigration†of cloud software on the industrial cloud platform, relying on industrial PaaS. The industry mechanism model on the “growth†of “indigenous residents†has fewer industrial apps, and the phenomenon-level industrial APP is scarce.
On the one hand, the number of industrial APPs developed based on the industrial PaaS platform is small. According to GE's forecast, the industrial Internet platform will experience explosive growth similar to the consumer Internet platform by 2020, and the total number of industrial applications on the Predix platform will exceed 500,000. According to the data released by China's leading industrial Internet platform companies such as Aerospace Cloud, Haier, Shugen Interconnect, Dongfang Guoxin, Xugong Information, UFIDA, Suowei, Tsinghua Unisplendour, Inspur, Zhejiang University Central Control, and Smart Cloud, the number of industrial APPs in China is not More than 5,000, it is far from being able to meet the needs of enterprises. Many of the 5,000 industrial apps are clouded from traditional software. They can only be regarded as “immigrants†on the industrial Internet platform. There are only a handful of industrial APPs that “grow†from the industrial PaaS platform.
On the other hand, the industrial Internet platform has not yet cultivated the emergence of image-level industrial APP. The US startup Uptake has developed an industrial app for condition monitoring and failure warning around Caterpillar Construction Machinery, accessing more than 3 million construction machinery, and the company's current valuation has reached $2.3 billion. Up to now, although many enterprises in China are working hard to build a cross-industry and inter-disciplinary industrial Internet platform, no one has developed an image-like industrial APP to detonate the application and promotion of the industrial Internet platform.
The industrial Internet platform has a large span and a complex system. From technology, industry to application, it is in the early stage of development. To build an internationally competitive industrial Internet platform, it needs strategic strength. It needs to adhere to government guidance and market leadership. It needs 10-15. Years of hard work.
(1) Complementing the short board and consolidating the "one hard, one soft, one net, one safe" four baseThe industrial Internet platform is not an isolated technology, but a comprehensive technical system. It is a gathering of modern information technology. At present, we must focus on the "four hard, one soft, one network, one security" four bases, and increase support. Promote the development and industrialization of key technologies. The first is to enhance the ability of automatic control and sensing industry support, and accelerate the development and industrialization of intelligent sensors, programmable logic controllers, distributed control systems, data acquisition and monitoring systems. The second is to implement industrial technology software engineering, and promote the research and development and industrialization of core technologies such as industrial cloud operating systems, new industrial software, industrial big data modeling and analysis, and micro-service components. The third is to strengthen the network foundation of the industrial Internet platform, promote the IP, wireless, flat, flexible technology transformation and construction and deployment of the plant intranet, accelerate the deployment of new network technologies such as NB-IoT, and accelerate the virtualization of software-defined networks and network functions. Such as the next generation of network technology research and deployment pilot. The fourth is to build an industrial Internet security system, strengthen the security of equipment, network, control, applications and data, and achieve comprehensive protection of industrial production systems and commercial systems.
(2) Building an ecological and vigorously cultivating an open source community and developer of the industrial Internet platformIn today's era, software open source and hardware openness have become an irreversible trend. Controlling the open source ecosystem will become the focus of the global industrial Internet platform. First, it is recommended to cultivate open source communities, guide automation enterprises to open various standards-compatible, protocol-converted technologies, realize the orderly flow of industrial data between multi-source devices and heterogeneous systems, ensure that industrial equipment “connects†and guides industries. Internet platform enterprises open development tools, knowledge components, and algorithm components to build an open, shared, resource-rich, and innovative industrial APP development ecosystem to ensure that the model industry mechanism model “followsâ€. The second is to speed up the construction of the talent team of industrial APP developers, support the industrial Internet platform enterprises to hold the developer entrepreneurial innovation competition, create a new ecosystem of “double innovation†based on the industrial Internet platform, and promote the “upper quantity†of industrial APP in a short time.
(3) Re-testing, insisting on the coordinated development of the platform platform for platform constructionAdhere to the "building platform", "using the platform", "measuring platform" to promote synergy, while building, testing, and promoting, to build and test, to promote use, to create a platform with rich functions and massive use of two-way iteration, mutual promotion A virtuous cycle. First, cross-industry cross-sector industrial Internet platform cultivation, it is recommended to refer to the national manufacturing innovation center cultivation method, introduce the selection criteria of the industrial Internet platform, adhere to the principle of "one thing, one discussion, mature one, one selection", and cultivate 10 in three years. Home cross-industry cross-domain platform. Second, in the application and promotion of industrial Internet platform, it is recommended to strengthen the linkage between the provinces and provinces, and select a number of provinces with high enthusiasm and good cloud-based enterprises as the demonstration provinces for industrial Internet platforms, and promote the “block economy†industrial clusters in the demonstration provinces. The business as a whole on the cloud. The third is to test and test the industrial Internet platform in terms of test and testing, such as device protocol compatibility, platform functional integrity, data security, etc., providing basic support for large-scale application of industrial Internet platform.
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