The industry 4.0 era is not a change in the whole world, it will affect the entire industrial production process, and thus affect people's lives. I can't imagine how intelligent the earth will be in the era of Industry 4.0. In recent years, China's intelligent manufacturing technology and its industrialization have developed rapidly and achieved remarkable results. Emerging science and technology such as intelligence and industrial automation have been integrated into industrial development, and we have achieved great results compared with developed countries. However, as far as the current status of China's smart manufacturing is concerned, the gap between China and developed countries is still very large. If we look at China's smart manufacturing in a more macroscopic scenario, we will find that many constraints affect its development. . In view of this, we also need to think and think in the process of developing intelligent manufacturing. I. Production mode and material constraints In this paper, we clarify that intelligent manufacturing is guided by the product strategy of “individualized productionâ€, which enhances the competitiveness of enterprises. Information technology is used to transfer data from all aspects of production to the management system, and “optimize†through dynamic optimization. Quality, reduce costs, and shorten product delivery cycles." Mechanical rigidity At present, the production methods of many industries are mostly for the existing raw materials, whether metal materials, plastic materials, fiber materials or semiconductor materials, through certain cutting, forming, weaving and other processes, and many of these processing are mechanical. There are restrictions. For example, pharmaceuticals, we can't carry out “plug-in†to achieve flexible customization, because each batch of drugs needs to be cleaned and produced in order to carry out another production. Many parameters that affect the quality of production cannot be adjusted online, which will inevitably lead to the production. Bad products, and quality iterations require batch-based data to achieve improvement. Research on the fusion of materials technology and manufacturing 3D additive printing technology in intelligent manufacturing is a hot spot in China's intelligent manufacturing, but there are still bottlenecks in terms of materials, processing speed and cost. There is no breakthrough in material technology, and traditional production processes cannot achieve breakthroughs. For example, the most effective way to save energy is process energy saving – through the complete improvement of the process, the new production mode is used to reduce energy consumption. But improving the process is difficult. An example is that digital printing is very good, but there is no innovative progress in the material and processing of inkjet heads. Domestically, new progress in the manufacturing field cannot be achieved in this direction. Others like ink technology, viscose technology, high-performance metal materials, special fiber materials, etc., have similar problems in their respective application fields. The lack of innovation in basic and new materials will result in our manufacturing industry still being subject to people in these areas, unable to truly upgrade the manufacturing industry, and have stronger capabilities in information and automation, and will not be able to produce more competitive products. Second, the current situation of information fusion constraints Data is not effectively collected and stored by the system At present, in the process of advancing the smart factory, we will find that the original equipment is from different manufacturers and different generations, which makes it impossible to interconnect the factory equipment. On the controller, the data of the traditional production such as the deviation of the printing color and the influence value, the yarn CV value, etc. can not be effectively collected. Many times, this situation is not caused by a technical blockade. Suppliers are certainly not willing to open up core technologies, but in many cases, these parameters are not considered at all in the traditional production mode, resulting in a large amount of data was wasted and no effective acquisition was achieved. The inability to connect and interoperate is only one of the constraints, but it is relatively easy to break through. Information model In the data line interconnection upgrade of many enterprises, there is a lack of information model, so there is no effective standardization and application software support for what kind of data is collected and how to use the data. Integration of informationization and automation In the integration of informationization and automation, the most common phenomenon is that in many factories, the management system uses the most famous SAP/ORACLE ERP system, representing the world's top management level, using the most automated production line. . However, these information systems and automation systems are like people from two worlds. They don't know each other and speak different languages. The effect of integration is not satisfactory. The reason is that many companies do not have a clear intention of industrial upgrading, just because the boss said, "our peers are doing smart manufacturing, we have to go to the intelligent manufacturing system", just to upgrade and upgrade, this upgrade investment, the effect The discount is expected. Advancement of intelligent algorithms After data collection and transmission, the data reaches the so-called cloud platform and big data platform. How is this data analyzed and optimized? The traditional expert system uses a project similar to Deep Blue and has accumulated decades of experience in data accumulation and processing. Therefore, without decades of accumulation, intelligent manufacturing is still unable to achieve "smart optimization and decision-making." Third, the constraints of management upgrade Lean production “Lean†is the foundation of digitalization, and there is already a lot of consensus, including those who are now investing in smart manufacturing projects. However, the foundation of lean production has been in Japan for decades, and it has been applied to China's intellectual creation, but it seems to be a bit of a quick success. In fact, if you go to some enterprises, even large enterprises, you will find that there is still a lot of “waste†in the quality control, storage material management, energy management, and asset maintenance of manufacturing – if you use lean production standards. Looking at these problems, we will find that the space for improvement within the manufacturing industry is still huge. Mining only in the existing production links can still bring huge benefits, which can improve the quality of the products and the production costs. reduce. Organizational design In addition to the benefits of lean manufacturing and smart manufacturing for the future, we will also find that the organizational structure of the vertical business unit of the original enterprise also constrains the smooth development of smart manufacturing. Because information collection and sharing is required, it is not only data but also the reorganization and optimization of business processes. The traditional enterprise organizational structure can no longer meet the needs of new intelligent manufacturing for information flow, and the resulting new definition of responsibility and changes in internal decision-making mechanisms. Based on this reality, breaking the boundaries of the department and making the management structure flatten, the internal information flow of the more "networked" organization can adapt to the network interconnection characteristics of intelligent manufacturing. Otherwise, the overall system will not operate normally. Cooperation strategy In the era of intelligent manufacturing, the obvious trend is that enterprises are no longer individual competitions, but competition of enterprise alliances. Organizations that still rely on their own power to form monopolies will be gradually marginalized in future synergies, and new businesses. The ecosystem is being built. How to share internal information more effectively, how the new cooperation model is more clearly defined and practiced, is the direction that needs to be explored. Fourth, the constraints of personnel training and education Innovative talent The innovation drive has been talked for many years. However, in the absence of talent and open system support, the so-called innovation is nothing more than “new bottled old wineâ€, lacking essential changes. For the intelligent process of manufacturing, the use of traditional thinking to understand the future of intelligent manufacturing can not promote the development of the entire manufacturing industry. Smart manufacturing does not mean machine substitution. Robots can't completely replace artificial, and the development of intelligent manufacturing and robots is inseparable from professional technicians. The new industrial ecology that is spawned requires a large amount of suitable labor. Therefore, if the intelligent talent support cannot be formed, the enterprise may fall into the transformation trap: there is a smart factory, but no one operates. The "Internet" and intelligent manufacturing era have higher requirements for the knowledge structure of technical skills talents. However, the common dilemma faced by enterprises is that the quality of students trained in colleges and universities is seriously out of touch with the actual requirements of enterprises. Many new formats have emerged. But the college does not have a related major. In a market-oriented environment, manufacturing companies should actively cultivate and introduce innovative talents. Although such investment is not the strength of every enterprise, some leading enterprises can take the lead in doing so. In addition to cultivating and introducing innovative talents, how to integrate talent resources is also critical. This requires us to have a top-level design, namely system design and system design, so that manufacturers in all walks of life will be motivated. Global talent training Intelligent manufacturing requires architectural design, which requires structural thinking and integrity and continuity of problem analysis, from the formation of each department of the group to the development of products and technologies. The lack of these kinds of thinking will lead to the phenomenon of "worrying out of one", "stretching" and "striving" from the top-level design to the bottom-level realization of intelligent manufacturing. If the overall structure operation mechanism design is not formed, it will also cause sequelae such as “repetitive investmentâ€, “project rework†and “unresolved substantive problemsâ€. It can not only become the direction of intelligent manufacturing efficiency improvement, but limit the company's upgrade speed. Fifth, the platform architecture lacks constraints In the Chinese manufacturing process, we value the investment in visible hardware, but we still have a lot of weaknesses in the software development platform. The biggest feature of intelligent manufacturing is the "integration" feature, and the integration will definitely need to be based on the "platform". Development platforms such as AutomaTIonStudio and Siemens Portal, especially Pro-e, Solidworks, CITIA, etc., which lack the integration of simulation, design and manufacturing, form the paradox for the “integration†required for intelligent manufacturing. Sixth, security risk constraints Security includes not only technical information security issues, but also administrative security issues, including security issues at the legal level. Information security risk Information security is first of all the "attacked" and virus protection issues that we talk about. These are only technical issues and can find effective solutions. In the era of big data, the definition of the right to use data will be more clear. How information is managed and how it works as the most important asset still lacks regulatory definition. Security issues in smart manufacturing have caused widespread concern in Europe. Basically, most equipment manufacturers are developing functional safety systems and have already applied them, and our investment in functional safety is relatively small. This is largely due to our lack of understanding of security issues. Traditionally, we believe that system security will not have direct output. In fact, for the interconnection of the era of intelligent manufacturing, the security of one unit will affect other production units, and the downtime of a certain machine will cause huge waste of association. Therefore, the security of the integrated system becomes an urgent concern. Of course, many security issues are themselves due to lack of foundation, not yet developed to a higher degree of automation, or not upgraded to the process of information integration. A clear understanding of the security system also constrains our smart manufacturing process. Intelligent manufacturing also needs the support of national funds and policies. This is also a constraint. However, if we can pay enough attention to and pay attention to the above six restrictions, it will be enough to make our development in the smart manufacturing industry relatively more solid. . digital whiteboard,interactive whiteboard for classroom,electronic whiteboard,digital board for teaching,smart board for teaching Guangdong ZhiPing Touch Technology Co., Ltd. , https://www.zhipingtouch.com