Big data has become the strategic commanding height of national competitiveness. At present, the world is in a new round of scientific and technological revolution and industrial transformation. By analyzing the massive data generated by the new generation of information technologies such as the Internet and the Internet of Things, we can sum up experience, discover laws, predict trends, assist decision-making, expand human ability to understand and transform the world, and provide a powerful engine for human economic and social innovation and development.
Big data has opened up a new way for the transformation and upgrading of manufacturing industry. In the era of data explosion, more and more data are obtained, managed and used by manufacturing enterprises. If we can scientifically collect, organize, analyze and utilize the data and provide valuable decision-making reference for the whole product life cycle and all aspects of enterprise production and operation, we can improve the productivity, profit margin and comprehensive development level of enterprises.
China has a comparative advantage in developing manufacturing big data. China's manufacturing industry ranks first in the world. There are a large number of manufacturing enterprises above designated size, and the level of information development is improving day by day. A large number of manufacturing data are generated at all times, with rich application scenarios and broad development space. In order to speed up the pace of building a manufacturing power, the State Council has successively issued policy documents such as Made in China 2025, the State Council's Guiding Opinions on Actively Promoting internet plus Action, and Action Plan for Promoting Big Data Development in recent years, which has also created a good development environment for the development of manufacturing big data.
Big data promotes the comprehensive transformation and upgrading of manufacturing industry.
Big data accurately responds to user needs and improves the R&D and design level of manufacturing industry. The application of big data in R&D and design can promote the creation of an integrated innovation platform, extensively collect and mine consumer behavior data and feedback information, more accurately grasp the use preferences of a large number of consumers, and bring consumers into innovative activities such as product demand analysis, R&D and design by crowdsourcing. In order to promote the continuous improvement of product design scheme.
Big data realizes business scenario interaction and promotes intelligent upgrading of manufacturing industry. If the traditional automation, digitalization and networking provide "limbs", "senses" and "nerves" for the manufacturing industry, then the application of big data gives the manufacturing industry a "brain", enabling it to flexibly respond to various business scenarios and realize real intelligence. Through the integration and analysis of manufacturing equipment data, product data, order data and data generated in the production process, production control can be carried out more timely and accurately, and the synergy and flexibility of manufacturing can be significantly enhanced.
Big data helps enterprises make scientific decisions and improve manufacturing management capabilities. The application of big data can promote the establishment of cross-industry and cross-regional innovation organizations and the development of new models such as collaborative design, e-commerce and crowdsourcing, and enhance the management ability of manufacturing enterprises.
Big data supports the development of production service industry and accelerates the service process of manufacturing industry. There are three main directions for big data to accelerate the service transformation of manufacturing industry: first, extend the business of enterprises from product production and sales to production-oriented services; The second is to change the enterprise development mode from providing after-sales service around product production and sales to providing continuous service for product design; The third is to change the main profit source of enterprises from product manufacturing and sales to after-sales production services.
The accelerated integration of big data and traditional business has spawned new products, new services and new formats. China has the largest consumer market and the most diversified consumer demand in the world. Integrating big data into the functional development of wearable devices, household products and automobile products can promote the leap-forward innovation of scientific and technological products, form new areas of manufacturing development such as smart wearable devices, smart homes and intelligent networked cars, and help to seize new growth points and commanding heights in manufacturing.
Promote the integration of big data and manufacturing.
At present and in the future, efforts must be made in the following aspects to promote the deep integration and development of big data and manufacturing.
Improve the industrial information infrastructure. Accelerate the establishment of industrial broadband networks with larger capacity and more reliable service quality, strengthen the planning and layout of wireless broadband networks in the manufacturing sector, and deploy low-latency and highly reliable industrial Internet for intelligent manufacturing units, smart factories and Internet of Things applications. Give full play to the advantages of internet enterprises and industrial software enterprises, guide them to closely integrate with manufacturing enterprises, and realize unified data collection, management and efficient processing.
Constructing manufacturing data resources. Promote the large-scale application of data acquisition terminals such as sensors, and collect data through multiple channels and levels. Guide and support key enterprises and industry organizations to build low-cost and high-efficiency manufacturing big data storage centers and analysis centers, and gather to form systematic, comprehensive, timely and high-quality data resources. Improve the relevant systems and mechanisms of manufacturing data resources construction, innovate policy incentives, and form an active, mutually beneficial and win-win data resources construction ecology.
Break through the core technology of manufacturing big data. Open independent and controllable manufacturing big data platform software and application software in key areas and key business links, support innovative small and medium-sized enterprises to develop specialized manufacturing data processing and analysis technologies and tools, and provide characteristic data services. Promote multidisciplinary cross-integration, and carry out research on key algorithms and key technologies of manufacturing big data analysis.
Improve the application ability of big data analysis. Build a number of high-quality manufacturing big data service platforms, promote open access to software and services, design and manufacturing resources, key technologies and standards, and enhance the application capability of manufacturing big data.
Ability to improve data security. Study and formulate the construction of big data security system for information collection and control and sensitive data management in the manufacturing sector. Study and formulate data classification standards, and promote standardization and legislation in data protection, personal privacy, rights and interests of data resources and development and utilization. Formulate and issue management standards for the collection, transmission, storage, backup and migration of manufacturing data, effectively ensuring the safety and reliability of all stages and links in the whole life cycle of data.
Cultivate compound big data talents. Support qualified universities to combine the advantages of computer, mathematics, statistics and other related majors to open big data-related majors. Encourage universities, scientific research institutions and enterprises to introduce big data-related strategic scientists and innovative leading talents in a planned and hierarchical manner, and rely on R&D and industrialization projects in the field of manufacturing big data to introduce high-end talents such as big data managers and big data analysts with practical experience.