Although China's process industry has made considerable development and progress in recent decades, there is still a certain gap between the overall production and manufacturing efficiency and the international advanced level, and the level of innovation under the constraints of resources, energy and environment needs to be improved.
backgroundSome developed and developing countries are currently accelerating the strategic planning and deployment of smart manufacturing, such as the US SPM plan, German industry 4.0, Japanese manufacturing strategy, EU future factory plan, Indian manufacturing plan, Chinese manufacturing 2025 strategy, the fourth industrial revolution Has come.
One of the cores of the fourth industrial revolution is the construction of cyber-physical systems (CPS).
CPS is a multi-dimensional and complex system of computing, network and physical environment. Through the organic integration and in-depth collaboration of 3C (computer, communication, control) technology, it can realize the real-time perception, dynamic control and information services of large-scale engineering systems. The realization of CPS can organically integrate computing, communication and physical systems, thereby improving the reliability, efficiency, real-time and robustness of large-scale engineering systems, and has important and extensive application prospects.
The CPS system includes environmental awareness, distributed computing, network communication, and system control issues, enabling the physical system to have functions of computing, communication, control, remote collaboration, and autonomy. It focuses on the close integration and coordination of computing resources and physical resources, and is mainly used in some intelligent systems, such as device interconnection, unmanned driving, IoT sensing, smart home, smart robots, and smart navigation.
According to the understanding of Yijin Manufacturing Institute, intelligent optimized manufacturing in the process industry faces three major international difficulties. Domestic and foreign researches are almost at the same starting line. The performance is as follows:
1. Due to the variable and unpredictable properties of raw materials, and the complex physical processes and chemical reactions involved in the processing process, the production process is difficult to describe with accurate mathematical models, and digitalization issues have a long way to go;
2. Unlike discrete manufacturing, the manufacturing process of the process industry generally has multiple interconnected processes, and the global optimization of its overall operation is a mixed, multi-objective, multi-scale dynamic conflict optimization proposition;
3. The current information network system architecture cannot provide the self-awareness, self-calculation, self-organization and self-maintenance functions for the optimization of production and business decision-making.
VisionThe intelligent optimized manufacturing with the theme of high efficiency, green and intelligent in the process industry is to realize the "four modernizations" at the engineering technology level, namely: digitalization, intelligence, networking and automation; at the same time, manufacturing in the enterprise At the operational level, the "four modernizations" must also be realized, namely: agility, efficiency, greenness and safety.
In the "Internet +" era, the vision and goal of intelligent optimized manufacturing in the process industry is: on the basis of the existing physical manufacturing system, fully integrate human knowledge, apply big data, cloud computing, (mobile) network communication and human-computer interaction Modern information technology such as knowledge-based work automation and virtual manufacturing, starting from the optimization of the entire process of production, management and marketing, promotes intelligent optimized manufacturing of process industries with the goal of high efficiency, green and intelligent, and not only realizes the equipment intelligence of the manufacturing process It also needs to realize the self-adaptive and intelligent optimization of manufacturing process, operation mode, and management mode, so as to maximize the economic and social benefits of the enterprise.
Basic theory and key technologyThe engineering scientific problems of intelligent optimized manufacturing in the process industry that need to be solved at present include: intelligent perception and integration of information in the whole process of production and operation, knowledge-driven production process planning and management decision-making, the entire process of collaborative control and optimization of human-machine-object collaboration, and Life cycle safety environment footprint monitoring and risk control, etc.
For these scientific problems, we need to solve and break through: special parameter in-situ detection and full-process ubiquitous perception, unified representation and distributed processing of multi-source and multi-scale information, knowledge-driven resource optimization and autonomous decision-making, and big data-driven enterprise production Difficulties in smart management, multi-dimensional intelligent modeling of the production process, etc., in order to optimize the overall operation behavior of the entire production process.
Through the deep integration of informatization and industrialization to achieve intelligent and optimized manufacturing of process industries, there are still some major basic theoretical and engineering scientific and technological issues that need to be resolved, such as business decision-making, resource and energy structure configuration, production planning and scheduling, and optimization control system instructions are still dependent Human experience is far from realizing the optimization of the overall operation behavior of the entire production process. Production process research and new product development still remain in production trials and experimental small trials, far from realizing virtual manufacturing.
At the same time, intelligent and optimized manufacturing in the process industry needs to further integrate physical devices, information and society in order to further improve the quality of employees, ensure safety and environmental protection, and form good social benefits.
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