In recent years, smart manufacturing has become a hot issue of common concern in academia and business. Despite this, people’s understanding of the concept of intelligent manufacturing itself has not reached a consensus, and there are many vague understandings. The promotion process of the business community is more complicated. This article analyzes and discusses these issues.
Smart manufacturing concept
” Intelligent Manufacturing ” in Chinese corresponds to two English expressions, namely smart manufacture and intelligent manufacture. Among them, the formulation of intelligent manufacture appeared earlier, but in most cases it refers to smart manufacture. In the China Academy of Engineering’s “China Intelligent Manufacturing Development Strategy Research Report”, intelligent manufacturing is divided into three progressive development paradigms: digital manufacturing, digital networked manufacturing and a new generation of intelligent manufacturing. Smart manufacture mainly corresponds to digital networked manufacturing, while intelligent manufacture corresponds to a new generation of intelligent manufacturing.
In the report of the party’s 19th National Congress, it is clearly pointed out that the application of the industrial Internet should be promoted. The focus is on promoting digital networked manufacturing. Therefore, it is necessary to further explain the smart manufacture. Its literal meaning is to give companies the ability to respond quickly to internal and external changes. The quick response is important because of the increasingly fierce market competition, making response speed more and more important.
From a goal perspective, smart manufacture is similar to flexible manufacturing. However, from the perspective of means, the former focuses on the application of ICT (information and communication technology). Compared with traditional informatization, it is often necessary to transform equipment, organization, processes, working methods, business models, etc., rather than pure ICT technology applications. Therefore, smart manufacture is often understood as the “deep integration” of ICT technology and manufacturing. In general, smart manufacturing involves not only manufacturing-related processes, but smart services and smart products are often included in the scope of smart manufacturing.
The four basic points can be used to understand the inherent logic of intelligent manufacturing: the in-depth application of ICT technology is the starting point of intelligent manufacturing; value creation is the purpose and destination of intelligent manufacturing; rapid response change is the external feature of intelligent manufacturing; synergy, sharing and reuse It is the internal mechanism for intelligent manufacturing to create value.
1) Emphasize that “the in-depth application of ICT technology is the starting point of intelligent manufacturing” because the historical opportunity of intelligent manufacturing is brought about by the development of ICT technology. It is necessary to avoid confusing intelligence with traditional automation and informationization, thus ignoring the real Intelligent work, opportunities to lose history. The idea of intelligentization is not unique now, but only in the highly developed conditions of ICT technology, the past ideas can be technically and economically feasible.
2) Put forward the background that “value creation is the purpose and destination of intelligent manufacturing”, and it is against the use of technology for technology and blind use of advanced and useless things. This kind of worry is not “awkward and worrying,” but it has the potential to spread. To this end, smart manufacturing must serve the real business needs of the enterprise. The demand for intelligence in many companies is implicit. Advancing smart manufacturing often requires enterprises to transform and upgrade, change production and management methods, and then find suitable scenarios to create value. This is the meaning of “deep integration” between ICT technology and industry.
3) “Rapid response changes are external features of smart manufacturing.” As competition continues to increase, the importance of rapid response is growing. For example, in mobile phones, automobiles and other industries, the value of rapid response is reflected in the speed of new products. The speed of launching a new generation of products largely determines the profitability of the company. In other industries that are sensitive to raw material prices, the ability to respond quickly to changes in the supply chain determines the profit and loss of the business. Therefore, one of the most important roles of intelligent manufacturing is to speed up the response.
4) “Collaboration, sharing and reuse are the internal mechanisms for intelligent manufacturing to create value.” ICT technology can significantly promote collaboration between people, machines and machines, people and machines, businesses and businesses, departments and departments. Reduce time delays and reduce errors on the interface. Cost, efficiency and quality can also be reduced by sharing material, people, knowledge or information. In the era of intelligent manufacturing, the reuse of knowledge has become more and more important. For example, through the reuse of modules, unnecessary time and capital investment in the development process can be reduced, and quality, cost reduction, economic efficiency, and rapid response can be supported.
There are many typical models or systems for intelligent manufacturing, the most famous of which are German Industry 4.0 and the US Industrial Internet.
Intelligent manufacturing and artificial intelligence, automation
With the rapid development of artificial intelligence technology, technologies such as image and speech recognition have begun to be widely used in the manufacturing process, which is of great significance to help human beings liberate from the boring and harsh working environment. Therefore, some people think that “smart manufacturing is the application of artificial intelligence in manufacturing.” But this view is not accurate and very easy to mislead the public.
Artificial intelligence traditionally has three schools. Symbolism, also known as the computer school, focuses on the logical reasoning function of the brain; connectionism, also known as the artificial neuron school, focuses on the structure of the simulated brain, is good at the study of knowledge; behaviorism, also known as the cybernetic school, focuses on the synergy of the simulated brain, Pursue the integration of knowledge and action. In many academic situations, artificial intelligence refers to the first two schools. The so-called “new generation of artificial intelligence” represented by deep learning is the development of the connection school.
However, the closest thing to smart manufacturing is the cybernetic school. The main idea of cybernetics can be traced back to Wiener’s Cybernetics in the 1940s. Wiener studied the difference between animals and machines. One of the distinguishing features of animals that distinguish them from machines is the perception and processing of information. Animals can sense their changes in the external environment at any time and adjust their behavior, unlike most machines. Execute in the order of the logical order. The essence of this theory is to unite the three elements of perception, decision-making and execution.
Wiener’s thinking promotes the advancement of theory and practice with the development of tools and means. “Perception” and “decision” are essentially information-oriented, while “execution” is ultimately directed at physical entities. Therefore, the unification of the two needs to link information to physics. This idea is reflected in the Watt steam engine. However, the perception and calculation of the steam engine is achieved by a physical entity such as a mechanical device. This implementation method is very clever, but it is not general and difficult to promote. This constraint until the emergence of weak electricity, information perception and calculation can be achieved with weak electricity, and converted into strong electricity to drive physical entities. Therefore, relying on the “electricity” approach, the information field and the physical field are linked. Cybernetics are produced in this context. In control theory, classical models are described by transfer functions and state equations. In a sense, the widespread use of this model is related to the original technical means, and the controller is often built with electronic components such as inductors and capacitors. Although this model is simple, there are still limitations in its application. In the era of computers, the mathematical models that can be described are greatly expanded and general. Later, the application of the Internet has greatly enhanced people’s considerable and controllable resources, and brought humanity into the era of intelligent manufacturing. Therefore, the theory of intelligence and automation is in the same vein, but the means of implementation have been greatly improved.
From the perspective of economics, the improvement of considerable and controllable capabilities has led to the strengthening of resource allocation capabilities, which in turn has led to economic improvements. Specifically, traditional automation is often limited to a small space, and intelligent manufacturing can achieve large-scale control and optimization across regions, departments, and even enterprises. For example, Shanghai Youyi Information Technology Co., Ltd. has worked in a steel mill in Shandong Province to realize real-time optimal control of gas producers, users and buffers. Although the technical principle is easy to understand, the related equipment is distributed within a few square kilometers, and the support from the Internet is not technically feasible. Therefore, the change of basic technical conditions of ICT is a key factor in promoting automation to become intelligent.
In contrast, automation is more important than substituting human physical labor, while intelligence is more important than substituting human brain labor, that is, decision making. This is also an important difference between the two. Therefore, the digitization, modeling, and software of knowledge and the promotion of machine cognition and decision-making ability are key technologies for intelligent manufacturing.
Typical genre of intelligent manufacturing: Industry 4.0
The concept of Industry 4.0 was proposed by the German Academy of Engineering in 2013. Its iconic features can be summarized as “automated assembly lines with individualized production capabilities.” This feature is a key to understanding Industry 4.0, linking the economics of technology to the need for technology to help people understand how Industry 4.0 harmonizes technical feasibility and economic viability. From a technical point of view, the production mode of Industry 4.0 inherits the advantages of low cost and high efficiency of the assembly line, and overcomes the shortcomings of poor flexibility of the assembly line in product changes. From an economic point of view, meeting individual needs can achieve better economic value. It is conceivable that if customized production is carried out by traditional production methods, product design, process design, time and economic efficiency of production organization are difficult to guarantee or even economical.
The production method of Industry 4.0 poses great challenges to the business of production organization, sales and procurement, and design services. And the intelligence is just right for these challenges. For example, through the reuse of modules and process knowledge, the time for R&D and trial production can be significantly reduced; the horizontal integration of information can meet the challenges of sales procurement and supply chain; the challenge of production organization management through vertical integration; through end-to-end Integration addresses the challenges of designing service business. For another example, personalized production leads to a very complex production organization and scheduling, which needs to be solved by using Cyber Cyber Physical System (CPS) technology.
Advancing Industry 4.0 is a long-term process, and companies must be driven by their own needs without being bound by the concept. The degree of automation and customization of the factory can be high or low, and the key is to promote the competitiveness of the enterprise. In fact, due to the uneven development of industry and region, the degree of automation, customization and difficulty are significantly different. For example, in the steel industry, advanced companies have the ability to customize production decades ago due to their high degree of automation, simple product switching, and relatively easy material tracking. However, in some discrete manufacturing industries, product switching is very complicated, and even pipeline transformation is required. In these industries, it is more difficult to drive automation, and it is even harder to be intelligent. In fact, Germany’s background in Industry 4.0 is primarily directed at these relatively difficult discrete manufacturing industries. In discrete manufacturing, the development of digital related technologies can make it difficult to solve difficult problems in the past.
There is a view that Industry 4.0 is the result of the maturity of Industry 3.0. It seems that this view is one-sided and may hinder people’s useful exploration. In fact, red-collar garments are personalized on a hand-operated assembly line, moving from Industry 2.0 to 4.0. The Siemens plant in Chengdu is known as the “Industry 3.8” factory, which can switch product types on the assembly line, but the manual operation of the factory is also very large. It should be noted that although both companies have a large number of manual operations, the logistics in the workshop is automated. Because the logistics of customized production is very complicated, without the support of automation and intelligence, it is difficult to manage well. This model has a certain representativeness and deserves a lot of business learning and attention.
Some people think that the development of Industry 4.0 to a certain extent will inevitably replace the industry 1.0~3.0. However, Industry 4.0 is only a significant achievement in the development of industrial technology to a certain extent. It does not mean that all enterprises adopt the production method of Industry 4.0. In fact, the high-end manufacturing industry in developed countries is not completely in the industrial 3.0 stage. Many high-end equipment and luxury goods are manufactured by hand. Moreover, industry 1.0~4.0 has advantages and will coexist for a long time. Therefore, whether the enterprise promotes the production mode of Industry 4.0 depends on whether it is economically profitable.
Typical genre of intelligent manufacturing: Industrial Internet
The Industrial Internet was a concept put forward by GE in the United States in 2012, which later affected companies in the United States and around the world. In contrast, the Industry 4.0 system is centered on the production process of the shop floor, while the Industrial Internet focuses on a greater range of synergies.
Industrial Internet thinking is produced in the course of practice. Maintenance personnel have long discovered that remote diagnosis of medical equipment via the Internet can significantly improve work efficiency and reduce maintenance costs. Later, some people used this idea for the diagnosis and maintenance of aircraft engine conditions. Similar cases have led to the emergence of industrial Internet thinking. Therefore, some people regard the “predictive maintenance” of equipment as one of the landmark scenes of industrial Internet technology applications. The Industrial Internet emphasizes the real-time connection of three elements: “smart machine”, “advanced analysis” and “staff”. Among them, intelligent machines are machines that install various sensors, controllers and software; advanced analysis is a data analysis algorithm that contains knowledge of various fields of expertise; workers refer to various types of staff involved in design, operation, maintenance, etc. through the Internet. .
GE Corporation of the United States recognizes that the Industrial Internet can help manufacturing companies extend and transform into the service industry. Therefore, GE is trying to use this trend to transform GE’s own manufacturing companies from “manufacturing companies” to “software companies” by helping other manufacturing companies transform. GE’s famous industrial Internet platform, Predix, was born under this idea. However, GE has been too eager to promote Predix, resulting in a technical input-output ratio is not suitable, and encountered a lot of trouble.
Intelligent manufacturing Chinese perspective
“Personalization on the assembly line” and “predictive maintenance of equipment” are often seen as “tag-like features” of Industry 4.0 and Industrial Internet. However, most companies do not necessarily need to be personalized, and most devices may not be able to perform predictive maintenance. These problems have caused confusion for many companies. Faced with these confusions, you need to think more deeply.
The purpose of human hard work is to make people themselves happier. When the economy develops to a certain extent, mankind begins to pursue a better working environment. At this time, the more humane working environment means more attractive to the best talents, so it can bring economic value to the enterprise, so we can analyze the future of the future industry from the perspective of how humans work.
In fact, there are many scientific and technological teams in China, and they have analyzed the development ideas of smart manufacturing in the future from the perspective of “people”.
The concept of a parallel system comes from the article “Parallel System Approach and Management and Control of Complex Systems” published by Wang Feiyue in 2004. Parallel systems use the “multiple world” perspective in complex systems research. When modeling complex systems, the degree of approximation with actual complex systems is no longer the sole criterion, and parallel systems are considered as a possibility for practical complex systems. The alternative form and implementation, the behavior of the actual complex system is “different” but “equivalent” to the behavior of the parallel system. For complex manufacturing systems, such as petrochemical production, machine tool manufacturing, etc., by establishing a manual manufacturing system that runs in parallel with the actual system, and virtual running and optimizing the production plan on the artificial system, using the virtual system to train employees, and predicting the actual system maintenance and maintenance nodes. Forming a parallel manufacturing system can save costs and improve efficiency for enterprises. In the parallel industrial era, on the one hand, enterprises can coordinate the internal process execution, manufacturing and resource scheduling of the management system by means of parallel evolution and closed-loop feedback of virtual and real systems. On the other hand, based on knowledge automation technology, the social intelligence service system transforms data into customer needs in real time, responds quickly to market changes, and simultaneously creates small and micro innovations and group intelligence to create products through task decomposition, rapid restructuring, and crowdsourcing. Thereby reducing the delivery time and increasing market share. At the same time, netizens can express their own personalized needs and ideas through the seamless connection of Internet of Things, Internet and mobile Internet. They can fully participate in the entire manufacturing process of product innovation, realizing real-time, personalized and large-scale “sensitive” mobile “ Intellectual creation.” This manufacturing model of the parallel industrial era is called parallel manufacturing.
In 2016, Ning Zhenbo proposed the idea of “three-body intelligence”, and observed the development path of intelligence from the perspective of the connection and integration between physical entities, conscious human bodies and digital virtual bodies. In 2017, Zhou Ji and others proposed the idea of HCPS (human-cyber-physical systems), suggesting that people can change the relationship between human and physical world through the Cyber space.
Compared with foreign related theories, these ideas have high similarity and focus on the role and role of people in the development of intelligent manufacturing. Although these ideas are abstract, they are operational. The logic of its development can be discussed from the application of the Internet.
With the development and widespread application of automation, human beings have gradually got rid of heavy manual labor. On this basis, people can gradually move away from dangerous and bad work sites through the Internet. In other words, the staff can control the physical world through the cyberspace.
When humans work in this way, they essentially act as decision-making algorithms. As a result, the possibility of computers replacing human decision-making is further enhanced. The basis of decision-making is knowledge and information, the subject with more knowledge and information, and the ability to make better decisions. In the traditional industrial stage, much of human information is obtained through the sensory organs, and the information obtained by the machine is limited. At this time, human beings have the advantage of information, so they have the conditions to make better decisions. However, under the new working mode, all the information that humans obtain from the scene is obtained from the computer, and the information advantage of human beings is no longer. At this time, as long as the computer fills in the shortcomings of “knowledge” and has the advantage of being more powerful and faster in processing information, it is possible to obtain a more significant “decision advantage”. Therefore, in the further development process, human beings will give more and more knowledge to computers. In addition, with the continuous accumulation of data, it will gradually enter the era of industrial big data, and the ability of computers to actively acquire knowledge will become stronger and stronger. In this way, the ability of machines to replace human decision-making will become stronger and stronger, and in some cases even beyond human beings. In this way, humanity will enter the “new generation of intelligent manufacturing” stage, or the real era of intelligent manufacture.
In this era, human beings will be free from real-time control of Cyber space, help to get rid of nervous and boring mental labor, and then engage in creative, perfect work on Cyber space, inject new knowledge into Cyber space.
To a certain extent, the intelligent manufacturing in the new round of industrial revolution is the comprehensive use of search technology, advanced manufacturing technology, social service applications (social media) and ubiquitous mobile terminal equipment, so that the public can participate fully through crowdsourcing. The whole life cycle of the product manufacturing process, real-time, personalized, large-scale innovation and “agile mobile intelligence”, or social intelligence. In the near future, the competitiveness and strength of a company may not depend to a large extent on its external scale and assets, but on its means and capabilities to control the cyber movement organization (CMO). Depending on its understanding, practice and efficiency of virtual and real interaction, it depends on the size and depth of the associated artificial enterprise. The deep integration of industrialization and informatization will inevitably be the application and popularization of parallel factories, parallel enterprises, parallel manufacturing.
Planning of intelligent manufacturing promotion path
“In-depth integration of ICT technology and manufacturing” is a perspective on smart manufacturing. However, many companies have found that with the use of robotic equipment, the cost has increased, but the benefits have not increased; collecting a large amount of data, but it is difficult to find valuable knowledge; reducing the work intensity of workers, but not producing more value. . This has caused many companies to get confused.
The essence of the above phenomenon is that the economy of the technology is poor and there is no economic success. In fact, advanced technology and good economy are not the same thing. The economist Schumpeter realized this problem very early. He pointed out that invention is not equal to innovation. Only when inventions are used for economic activities and success is innovation.
The key to promoting the healthy development of smart manufacturing is to make the technology economically sound. In order to improve the economy, the adoption of new technologies “to be charred in the snow, do not add icing on the cake.” When a company has a strong demand for technology, technology is economical. This principle is still true in the era of intelligent manufacturing.
Enterprise needs are not abstract, but come from specific business scenarios. Different business scenarios, the intensity of demand is different, and the value brought is different. For example, GE’s technology is economical for aircraft engines, but it may not be economical for use on cheap toy airplanes. From the trend point of view, the value of advanced technology used in high-end industries is large, and the value used in low-end industries is small. China’s low-end industries are large and large, which is why Chinese companies are more confused when they promote smart manufacturing.
Specifically, in view of China’s relatively low-end manufacturing industry and relatively low labor costs, smart manufacturing can’t just focus on letting machines replace people’s work, but also focus on helping people work more efficiently and make machines work. Better than people. In scenarios suitable for intelligent manufacturing, human work is often subject to physiological constraints, especially mental constraints. At this time, the technological advantages of intelligent manufacturing are easily transformed into economic advantages. The theory of intelligent manufacturing is directed at a complex Cyber space, involving extremely complex collaborative work and real-time mobilization of a large number of resources. At this time, the complexity of the decision-making process will impact the limits of human brains. Therefore, with intelligent means, it is possible to manage related issues better and thus create more value.
The confusion of Chinese companies is often because it is difficult to find a scenario suitable for intelligent manufacturing technology. In this regard, entrepreneurs should take the initiative to change the enterprise itself to create new business scenarios. This kind of work actually creates the right needs for the application of smart technology. This is the “deep integration” of ICT technology and manufacturing. The activity of “creating the scene” is essentially the so-called “transformation and upgrading”. Transformation and upgrading is the change of work flow, organizational structure, business model and business model. It is the reconfiguration of resources, as well as the improvement of quality efficiency and R&D services.
Intelligent manufacturing can promote enterprise transformation and upgrading. This phenomenon can be expressed from another angle, and the transformation and upgrading into intelligent manufacturing technology creates demand and suitable application scenarios. The significance of understanding from this perspective is that the promotion of intelligent manufacturing should first be a strategic issue considered by entrepreneurs, not a technical issue that technicians are responsible for. Technicians often only consider problems from the inherent business scenarios, and naturally encounter a lot of confusion. Entrepreneurs think clearly to create business scenarios that are suitable for smart manufacturing and create demand for technology. Of course, the transformation and upgrading of enterprises is not for the application of intelligent manufacturing technology, but for adapting to the needs of social development and market, and improving the economics of enterprises.
Enterprises promote the external environment of intelligent manufacturing
Many people realize that many ideas, theories and technologies of intelligent manufacturing are actually “not advanced”, which have been proposed, studied and practiced decades ago. This is exactly the case. Fundamentally speaking, it is not the human mind, but the social needs and technical conditions. These changes have led to a fundamental change in the economics of related technologies.
From the perspective of technical feasibility, with the development of ICT technology, the performance of computers and the Internet is getting better and better. In the past, many conditions that could not be perceived in real time and processed in real time have been implemented. At the same time, the reduction of related technology costs and the increase of Internet configurable resources have also reversed the technical economy of many scenarios.
From the perspective of demand, the country’s economic transformation, aging and other challenges have brought tremendous demand and motivation to promote smart manufacturing. In the past 40 years of reform and opening up, the middle and low-end manufacturing industry has been almost over-represented and market competition has become increasingly fierce. In this context, companies must improve quality, enhance innovation and service capabilities, and improve responsiveness. At the same time, the labor market has also changed from “unlimited supply” to “supply in short supply”, and the labor costs of enterprises have been rising. In the foreseeable future, the two trends will become more and more serious and affect the speed of economic development. If we cannot improve labor productivity and added value of products, China’s economic development will stagnate and even decline. This is the fundamental reason why China must promote smart manufacturing and accelerate the transformation and upgrading of enterprises.
The direction of enterprise transformation and upgrading must follow the laws of social and market development and avoid deviations from direction. In this regard, both social needs and technical capabilities require companies to pay more attention to product quality. Enterprises must abandon the past concepts of cost and light quality, and can not abandon the basic quality requirements to meet individual needs. In fact, personalization is often targeted at people with higher quality requirements. Therefore, using low-quality products to meet individual needs often runs counter to economics.
The transformation and upgrading of enterprises must also grasp the rhythm, combine specific national conditions, and not blindly reduce people and improve the degree of automation and intelligence. The relatively poor quality of workers and the relatively low level of management are common problems for Chinese companies. Some enterprises have far more mistakes caused by human factors than the profits of enterprises. Therefore, using intelligent technology to replace people, helpers, and managers, you will get good economic results.
However, people tend to cover up their own “runs and leaks”. Therefore, for managers, value loss is often hidden. To change these phenomena, companies often need to first change organizational processes and systems, and change the relationship of interests. This is also a transformational upgrade in nature.
In a sense, the application of transformation and upgrading and ICT-related technologies is two-pronged. However, in the actual operation process, it is implemented by people at different levels. If the synergy between the two is not well handled, it will be difficult to promote. Obviously, the purpose of enterprise transformation and upgrading is not to apply the relevant technology of intelligent manufacturing, but to adapt to changes in the market and the environment. Therefore, the direction of transformation and upgrading should first be grasped by entrepreneurs. From the perspective of technical economy, intelligent manufacturing is by no means a mere scientific and technological issue, but a problem of enterprise management and social development. Only in such a vision can we avoid one-sided understanding of the problem.
The purpose of intelligent manufacturing is to create value. The research on intelligent manufacturing should focus on how technology creates value, rather than indulging in academic concepts. This requires understanding the logic of intelligent manufacturing to create value. From a means of point of view, intelligent manufacturing can be seen as a deep integration of ICT technology and manufacturing, that is, using ICT technology to improve the economics of business-related businesses. The way to improve economics is generally to promote multi-party collaboration, resource sharing, and knowledge reuse in business-related business activities.
The advancement of smart manufacturing is often a difficult process that is often accompanied by a process of enterprise transformation and upgrading. Technology applications are costly. Only when the technology is used in the right scenario can the value created exceed the cost. For many Chinese companies, such a scenario does not exist in the sky and needs to be created through transformation and upgrading.