The most popular things to help China's smart manu

2022-08-08
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Assist China in intelligent manufacturing and industrial big data

industrial big data; Intelligent manufacturing; Information Delivery; Industry information; At present, major countries in the world have launched a new round of industrial revolution characterized by the integration of information technology and manufacturing industry, accelerated the development of a new generation of information technology, and promoted its in-depth integration with the global industrial system, in order to seize the commanding height of a new round of industrial competition. Industrial big data will play an irreplaceable role in the revitalization of the manufacturing industry in old European and American countries and the transformation and upgrading of China's manufacturing industry

what is industrial big data

industrial big data refers to all kinds of data and related technologies and applications generated in the whole product life cycle from customer demand to sales, orders, planning, R & D, design, process, manufacturing, procurement, supply, inventory, delivery and delivery, after-sales, service, operation and maintenance, scrapping or recycling and remanufacturing around the typical intelligent manufacturing mode in the industrial field. Industrial big data takes product data as the core, It greatly extends the scope of traditional industrial data, and also includes related technologies and applications of industrial big data

industrial big data has dual data, namely value attribute and property right attribute. On the one hand, key technologies such as industrial big data analysis can improve the intelligent level of design, process, production, management, service and other links, meet the customized needs of users, improve production efficiency and reduce production costs, and create quantifiable value for enterprises; On the other hand, these data have a clear ownership relationship and asset value. Enterprises can determine the specific use mode and boundary of the data, and the property right attribute of the data is obvious. In essence, the value attribute of industrial big data is based on the key technologies such as industrial big data collection, storage and analysis to enhance or realize the value of data in the process of industrial production, operation and maintenance and service; The property right attribute of industrial big data focuses on helping industrial enterprises to clarify the data asset catalog and data resource distribution, determine the ownership boundary, and provide support for the in-depth mining of its value through management mechanisms and management methods

background of industrial big data

in industrial production, data is generated from time to time. The speed, energy consumption, temperature and humidity of the production machine tool, the combustion and combustion of the thermal generator set, the equipment data of the automobile and the location and speed of the logistics team are all data in the production process

since industry has become a category independent of social production, the data collection and use scope of industrial production has gradually expanded. Because Taylor uses a stopwatch to calculate the time when workers use a shovel to send coal to the boiler, it is the collection and use of production management data, the hydration production of Ford Motor, the collection of industrial data in the automobile production process and the use of the factory. Toyota's lean production model extends the collection and use of data to factories and upstream and downstream supply chains; The complete automation of nuclear power production process will raise the automation level of production process data to a higher level

any data collection and use is expensive, and industrial data is no exception. However, with the development of information technology, electronic and mathematical technology, sensors, IOT and other technologies, a number of intelligent, high-precision, long-time navigation, cost-effective and micro sensors came into being. With the support of mobile data communication, the new generation network technology represented by IOT can collect and transmit data anytime and anywhere. The new data processing infrastructure represented by cloud computing has greatly reduced the technical threshold and cost of industrial data processing. Taking the SCADA system in the industrial field as an example, each power and chemical enterprise needs to establish a SCADA system with a cost of more than 10million yuan under the traditional mode. If the cloud architecture model is adopted, the cost will be reduced by more than 70% when the shell is installed on the printed circuit board

the change of social demand is the biggest driving force. In the era of commodity surplus economy, the consumption culture represented by personalization makes the output of industrial enterprises meet individual needs to the greatest extent. From clothing customization, vehicle matching, to T-shirt printing and personalized education

there are two ways to meet personalized needs. Taking clothing customization as an example, the cutting and layout of clothing are determined through teachers' ruler, hands, eyes and experience. This mode is called simulation mode, which is difficult to ensure the efficiency and quality of personalized customization, and can make the light uniform, soft, time-consuming and cost-effective. The other method is digital mode, that is, by developing a set of data acquisition means. The front office customer representative measures and collects the user's digital data, and then sends the data back to the headquarters. Combined with raw material data, the demand is decomposed into production process actions. Finally, we can produce clothes that meet the requirements of customization

of course, the factory will also employ senior masters. Their main work is not to face the customized needs of individual customers, but to study better production processes, control data and process decomposition. Under this mode, the efficiency and quality are guaranteed, and the efficiency increases linearly with the expansion of the production line. A group of expert groups continue to study and improve the process capability. Customized production costs will be greatly reduced. From the perspective of development trend, the personalized production of the latter digital mode will be the choice in the future

national policies are important influencing factors. German industry has completed the process of industrial automation. On the basis of automation and industrial data, cloud computing and artificial intelligence technology are introduced to improve the intelligent level of industry to meet the social demand for mass customization production. The United States has strong cloud computing, connectivity and data processing capabilities. On this basis, an industrial interconnection strategy is proposed to connect the data of a single device, a production line and a factory through big data. Excavate the value of industrial service industry in diagnosis, prediction, after-sales service, etc

compared with Germany and the United States, China is in the development stage of industrial automation and cloud computing. Therefore, it is suggested that the made in China 2025 plan will integrate industrialization and information integration through industrialization and information integration. Develop a series of key projects and promotion plans

status quo of industrial big data industry

industry is the foundation and pillar of the national economy and an important symbol of a country's economic strength and competitiveness

in recent years, industrial big data has attracted much attention as a key technical support for China's intelligent manufacturing and industrial interconnection and an important foundation for the integration of industrialization and industrialization. The CPC Central Committee and the State Council have issued a series of comprehensive policies and instructions on the integration of big data and industrialization, interconnection and manufacturing integration, which put forward clear requirements for the development of industrial big data and comprehensively guide the development, industrial application and standardization of industrial big data technology in China

from the supply side, the supply side capacity of industrial big data has been continuously improved, and a number of specialized, special and new enterprises have emerged, becoming the backbone to promote the development of industrial big data in China. First, with the development of digitalization, software and platform of traditional industrial manufacturing enterprises, a number of derivative enterprises with strong data aggregation capabilities have emerged, such as sky cloud, tree root interconnection, etc; Second, software enterprises have penetrated into the industrial field, and the emerging technology-based enterprises, such as Kunlun Zhihui and Dongfang Guoxin, have continuously broken through the core technologies in the fields of industrial data modeling, analysis and processing; Third, Internet enterprises actively entered the industrial field. For example, Alibaba launched products and services such as et industrial brain, and Tencent launched the industrial Internet cabin cloud platform

from the demand side, with the advance of national strategies such as intelligent manufacturing and industrial interconnection one by one, new models such as personalized customization, networking extension, intelligent design, production and service continue to emerge, and the demand for industrial big data technologies, products and platforms continues to increase, providing sufficient application scenarios for industrial big data

however, due to the addition of polylactic acid, while the development of China's industrial big data industry continues to be optimized and improved, it is still necessary to clearly recognize that China's industrial big data still has some problems, such as the lack of access to IOT data, inconsistent formats, unclear data property rights, difficult to break data barriers, and insufficient application of data throughout the industry chain. The main reasons are as follows: first, China's domestic industrial software and high-end IOT equipment are in short supply of core technologies, while the reading and writing of foreign equipment are not open, and the data cannot be read or the formats are diverse, so they cannot be used directly; Second, in the face of industrial data with large volume, wide distribution, complex structure and diversified types, the overall data resource management level of the industrial industry is insufficient at present, which makes it difficult to manage all kinds of internal and external data of the enterprise, let alone fully analyze and utilize them. Third, there is a lack of an available, easy-to-use and reliable industrial big data platform, which makes it difficult to make full use of the upstream and downstream data of the whole industrial chain to achieve a wider range of implementation links and intellectual interaction between various industrial elements, industrial business processes, such as people, machines and objects, and between upstream and downstream enterprises of the industrial chain, so as to promote resource optimization, collaborative manufacturing and service extension of industrial production

recently, the Ministry of industry and information technology issued the guidance on the development of industrial big data (Exposure Draft), which aims to promote the development of industrial big data, gradually activate the potential of industrial data resources, and continuously improve data governance and security capabilities. Industrial big data analysis is a process that uses statistical analysis technology, machine learning technology, signal processing technology and other technical means, combined with business knowledge, to process, calculate, analyze and extract valuable information and laws from the data generated in the industrial process. According to the Research Report on the prospects of China's industrial big data market in 19 years of 20 pairs of our experimental machine production released by China Business Research Institute, the scale of China's industrial big data market exceeded 15billion yuan in 2016, maintaining growth. It is estimated that the market scale will be nearly 50billion yuan in 2019. By 2022, the scale of China's industrial big data market may exceed 82.2 billion yuan; More than 190billion yuan in 2022

practical guidance of industrial big data

industrial big data is a major change in enterprise production and operation. For industrial enterprises that have not yet completed industrialization and informatization, the data age is coming again, and the challenges are also great

the construction of industrial big data is first of all a change in thinking, which has changed the previous industrial production mode dominated by factor competition and entered a new production era dominated by data and innovation competition. Secondly, as professor wangjianmin of Tsinghua University said, big industrial data has no turnkey project. It requires the joint participation of leaders, management, employees and relevant personnel to perform their respective responsibilities in order to achieve success

finally, industrial data construction has grasped two boards as a breakthrough. One is the longest board, that is, to find out the most competitive place of the product (industry), continue to deeply tap the potential data value, and build product and service capabilities around the industrial data in this field; The second is the shortest board. Where is the pain point that affects the development, cost, market, supply chain or energy consumption of industrial enterprises? In the data age, find solutions for big data opportunities

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