On the Three Stages of Development of Intelligent Manufacturing

The development of informatization in China in recent years has seen many concepts and hot spots, from cloud computing to the Internet of Things, smart cities to big data, and to the current wave of artificial intelligence. These heat waves must come down to serve the manufacturing industry. For the development of artificial intelligence in China, the most important issue is to solve the problem of China's manufacturing development. If the intelligence of the manufacturing industry does not go up, the backbone of the Chinese national economy will not be solid enough.

On the Three Stages of Development of Intelligent Manufacturing

The first thing to understand is what is smart manufacturing? According to the Wikipedia definition, intelligence refers to the ability to acquire knowledge and skills. The "artificial intelligence" has not yet been uniformly defined. This concept was first proposed by Turing in 1952. Nowadays, many people explain the artificial intelligence, the sentences are getting longer and longer, and the talks are getting more and more complex. At the end of the day, everyone is confused about what artificial intelligence is. In fact, artificial intelligence is simply to say that it is the function given to the machine by man. Specifically, through the computer's hardware and software, especially various kinds of software, the machine is given intelligence, so that the machine can feel the environment, aware of the changes in the environment, and further provide advice for policy makers, expand the intelligence of people, even Make decisions on your own in the case of prior authorization.

If intelligence is the ability to acquire knowledge and skills, it is undeniable that it is these computer-aided systems and industrial software that bring intelligence to manufacturing. Therefore, intelligent manufacturing, in a nutshell, is simply computer manufacturing, without adding too many modifications and too complex definitions.

The computer is more powerful than the human brain, not entirely because of its powerful computing power and storage capacity. The key is the software that runs. Without software, computers are just a bunch of metal plastic. Based on this, we can look at the development of manufacturing informatization, and we can actually understand the three phases of the evolution of smart manufacturing.

"Industrialization and Informationization"

The development of manufacturing informatization is mainly focused on the business operations of the company. The first is internal corporate information, as shown in the figure below. This includes "restructuring and recreating", that is, research and development of information, product information, production information, management information, and business processes and organizational reengineering. The product information, mainly refers to products with embedded systems, and their complexity varies. Understanding product information is very important for understanding the current smart manufacturing.

Figure | Internal Informationization

At the same time, the company also has a problem of upstream supply chain and downstream social relations. The upstream includes the recruitment of raw materials, spare parts, equipment, and personnel. The downstream is related to sales, banking, and customer relationships. These belong to the problem of external informationization of enterprises.

The internal business and external business of the company constitute the most basic connotation of enterprise informationization. The earliest start of enterprise informationization began with digitalization. When the computer was invented, it was originally a scientific calculation, and it was soon used for business processing to improve the management results. This is a process that develops from the bottom up. It begins with some data processing systems, such as financial management, including some statistical report processing; then, it gradually rises to the management level, that is, development management information system (MIS), from financial management. , personnel management, to production management, go up one layer; finally, rose to the decision-making level and development decision information system (DSS). The informatization of the enterprise was at the beginning of the digitization period.

Digital start

However, the use of computers to transform a company’s production equipment is actually starting earlier than managing an information system. In 1952, the second year of commercial electronic computer invention, a company in the United States designed a numerical control device and developed the first three-axis CNC milling machine. Although this milling machine is large and expensive, it opens up a new era of digital control. In 1958, the United States developed the first machining center. This means that computers have changed the era of manufacturing and formally kicked off. Subsequently, with the invention of the first micro-processing chip, various kinds and hundreds of millions of embedded systems began to be embedded in various equipment and various products. Manufacturing began to move toward the age of computer control with digital manufacturing as the core. At that time, the country was called mechatronics.

The formulation of "mechatronics" did not completely point to the essence of the problem. It was computer control.

It can be seen that computer systems have begun to give intelligence to various manufacturing equipments early on. If we follow the definition of smart, then the issue of smart manufacturing can be said to have been proposed very early. In the entire process of information-based manufacturing transformation, industrial software has supported the development of enterprise digitalization and has played a key role.

The recent television station had a discussion session on China's manufacturing industry. Among them, regarding the question of “What else can China's manufacturing industry fail to manufacture?”, ten aspects were mentioned, except industrial software. As everyone knows, China’s manufacturing industry ranks first in the world and accounts for 20% of the world's manufacturing industry. However, China’s industrial software is now more than 90% dependent on imports, and even more complex are not domestically produced. Moreover, the market share of China's industrial software accounts for only 1.7% of the world's industrial software market share. A 20% of manufacturing powers only accounted for 1.7% of the share, which is enough to show that the "constitution" of China's industry is too weak. It seems that there is still a big deviation in everyone’s understanding of this issue.

In fact, as early as the 1970s, we can see that the digitalization of the traditional industry is booming. In particular, in 1974, after the successful development of the fifth generation of computer numerical control devices using micro-processing chips and semiconductor memories, the development was very rapid from the perspective of production equipment. In terms of numerical control machine tools, from one axis to three axes to five to seven axes, a revolutionary influence was exerted on the information-based industrialization. There are also various computer-aided systems, from auxiliary CAD to computer-aided engineering CAE, to computer-aided manufacturing CAM, which have had a profound impact on the modernization of manufacturing and completely changed people’s industrialization of modernization. Awareness.

Later, with the development of computer technology, full three-dimensional digital and digital simulations have emerged. The digitization of the industry is moving toward the high end. From the time an order is received from the company to the final product delivery, the entire process relies entirely on the control and support of computer software.

The rise of networking

In the early 90s of the last century, the Internet began to spread around the world, and the network of enterprises also developed rapidly. Before the Internet was widely used, almost all enterprises adopted the client server (C/S) architecture, but the client server could only solve the networking problem of the local domain. After the rise of the Internet, remote areas can be networked, and companies are quickly becoming networked.

In addition to the application of the Internet, there are two main directions for the network of enterprises. One is the intranet, which connects all information systems of all departments and subordinate units within the company to one online network, whether these departments are in Beijing or in India. Or Mexico. This greatly improves the operational efficiency and effectiveness of internal business operations. Of course, only the exchange of information and data has been achieved, and intelligence has not yet been achieved.

The other is an extranet. The company’s external contacts are all conducted via the Internet. In other words, a part of the company's internal network is open to external cooperation units, and it is required to achieve horizontal communication. For example, if a car is produced, the production plan will be open to the seat factory in the upper reaches, and the latter can enter the internal network of the company to understand the production progress of the relevant departments so as to provide accurate and timely delivery. After the company is connected with the bank, the bank will automatically pay the upstream supplier as long as the seat is accepted by the automobile manufacturer. In this way, the integration of external information systems is achieved.

The networking of manufacturing and production brought about by the Internet is based on intranet and extranet implementations. This can be seen as the core connotation of the early "Internet + manufacturing." It can be said that "Internet + manufacturing" actually started in the 1990s.

The major technological breakthroughs brought about by the networking of manufacturing industry are at least reflected in the following three aspects.

The first is the associated design system. In the virtual design and manufacturing environment, the network can support hundreds of online users to design in real time at the same time, so that the three-dimensional design results between the overall and subsystems of a system or an equipment are related to each other. One of the fundamental driving forces behind IBM's early development of computer-aided design was that digital drawings could be transmitted over the Internet and parts could be produced at any of IBM's factories around the world. At that time, the design speed of new products was accelerated by 16 times, and the speed of product changes and updates increased hundreds of times. "Internet +" has opened up an unimaginable huge space for the improvement of manufacturing capabilities. It is a brand-new competitive advantage for enterprises.

The second is a networked collaborative platform. The network brings not only the exchange of information, but also the cooperation of engineering personnel. Some large companies, such as Boeing, have taken the lead in establishing their own very powerful networked collaboration platform. In September 2000, Boeing, Lockheed Martin, Raytheon, BAE, and R&R represented the United Kingdom’s aviation giant, which initiated the formation of the famous Exostar to explore the supply chain network collaboration of the defense aviation industry. Currently, there are six major manufacturers of supply chain management and collaboration through Exostar, covering 16,000 professional suppliers of different sizes. Subsequently, the four giants of the European defense aviation industry, Airbus, Dassault Aviation, Safran and Thales, also followed the footsteps of their US competitors and initiated the establishment of Boost AeroSpace, a networked collaborative manufacturing platform belonging to the European Defense Aviation Industry. In 2011, it officially provided services to customers in the industry.

The third is the full three-dimensional labeling technology. As long as any product is made from three-dimensional drawings, the drawings of the parts can be naturally decomposed and generated using computer software and systems. This allows companies to form a single data source management. The Digital Thread that the US Department of Defense and Aerospace has attached great importance to in recent years is precisely the development and extension of such a technology.

However, whether it is related design, networked collaborative platform, or full three-dimensional labeling, and the underlying support, it is not the network but the industrial software. All this is supported by a variety of industrial software. The reason why today's industrial products that China cannot yet produce can be very important is that there is no corresponding industrial software supporting manufacturing equipment. There are many core technologies that are difficult to break through in integrated circuits. Among them, the design of integrated circuits is an important part. The design drawings of high-end integrated circuits cannot be drawn manually. They are drawn by computer-aided design software. Without the most advanced such software, it is impossible to design the most advanced integrated circuits. If foreign countries only sell us the first two generations and the first three generations of design software, then China can only design the first two generations and the first three generations of related products. The importance of industrial software can be seen here.

Intelligent development

The development of enterprise intelligence can be traced back to the early 1960s. Through the intelligent development of the manufacturing industry in the figure below, we can see how manufacturing has gone from digital to networking and then to intelligence.

Figure | The history of the development of manufacturing intelligence

It can be seen that the intelligence of the manufacturing industry is basically synchronized with digitization, but in the early days, it was just a stand-alone machine and a single equipment. The very complicated software like CAE needs to integrate computing, engineering knowledge and human experience. Therefore, industrial software is not simply software but a science. Only engineers who learn computer software can't design advanced industrial software. In terms of intelligence, business intelligence is also a very important branch from the perspective of data processing.

The development of China's informatization over the past few decades has two shortcomings. A networked inward problem, many companies only made an intranet, almost no extranet, this situation is related to our national conditions. The second is the use of business intelligence in China's development is very slow, this may be because "shoot head to make decisions" has become a habit.

The notion that there is more speculation today is artificial intelligence. The most popular ones are deep learning and machine learning. This development is mainly based on two conditions: superior computing power and abundant large data sets. Now, on the one hand, the computer is running fast and the amount of storage is very large; in addition, many important data can be collected and processed. Such as voice recognition, image recognition, are not made today. As early as the early 60s of the last century, the Institute of Automation of the Chinese Academy of Sciences carried out research on pattern recognition. However, at the time, the data could not be counted on and could not survive. Therefore, the movement of artificial intelligence after the 1970s is not much. In the past few years, artificial intelligence has begun to heat up again because of the large amount of data and the speed of computers. Of course, artificial intelligence is not just about deep learning and machine learning. For example, human brain simulations, etc., and artificial intelligence are at a more advanced stage of development, and there will be greater development.

Intelligence is actually based on computational science, not just computer science. The United States National President’s Information and Technology Committee wrote a report to President George W. Bush in 2005 on the importance of "computing science." It said that computational science is made up of three different elements: computer and information science, and construction. Modeling and simulation software and computing infrastructure, these three are indispensable.

Intelligence in the sense of computational science actually includes four basic elements: models, algorithms, software, and data. To study any problem, we must first construct the mathematical model of the physical problem; afterwards, we need a set of algorithmic methods for model calculation, such as solving various differential equations and algebraic equations; we need to form software that can be used to perform calculations repeatedly according to the algorithm; When calculating, it requires a lot of data processing and analysis. If only information is collected, stored, processed, retrieved and used, this is not an intelligent system but a simple information system; even if they are connected to a network, it is still only a networked information system, not a Smart system. Therefore, to determine whether a system is a true, intelligent system must be evaluated from these four aspects. In many places, smart cities and intelligent manufacturing are used. If you need to carefully scrutinize its authenticity, the best measure is to use this rule with four dimensions.

On the Three Fulcrums of Intelligent Manufacturing

The basic understanding of the three stages of smart manufacturing was discussed above. However, how to implement smart manufacturing requires consideration of the three fulcrums of smart manufacturing: products, equipment, and processes.

Figure | The three fulcrums of intelligent manufacturing

The first thing to consider is what is the goal of promoting smart manufacturing. Obviously, companies are pursuing products rather than how fashionable they are. When companies sell their products, they don’t want to advertise how beautiful and modern the company’s production lines are, but they must explain the value of this product. Product is the performance of the enterprise facing the society. The goal of smart manufacturing is product, not smart manufacturing itself. Therefore, product intelligence is one of the top issues that companies must consider. If smart manufacturing fails to produce smart products, smart manufacturing loses its significance. Moreover, if the company's products are not intelligent, there is a great possibility that products and companies will be eliminated in the future.

The second fulcrum is the equipment on every key link in the equipment and production process (including R&D and design). It must be intelligent. If this intelligence cannot be achieved, labor productivity and labor efficiency cannot be greatly improved, and companies may not be competitive. Not digital, networked, and intelligent production equipment is not the advanced manufacturing equipment of this era. Moreover, if the device is not intelligent, it may not be able to produce intelligent products that the company wants to produce.

The third fulcrum is the intellectualization of the company's production process. The intelligent solution of equipment is the intelligent problem of “spots” in the production process; enterprises can realize the overall intelligence of the enterprise only if they realize the intelligence of the whole production process, and can achieve the maximization of intelligent benefits.

Smart product is the first fulcrum

If a machine tool manufacturing plant, production equipment and process are all intelligent, and the machine tool it produces is a general machine tool, there is no intelligent element, so the future of this machine tool plant is very worrying. Because, he himself will not buy such an intelligent machine.

Therefore, when considering the development of smart manufacturing, any enterprise should first think of how its products are intelligent. Even if the production process is not partially or fully intelligent and intelligent products can be made, then companies should first consider the issue of product intelligence.

The intelligence of products is achieved through the inclusion of various computer systems with varying degrees of complexity, especially embedded systems. The embedded system can not only become the most important and representative technology of intelligent manufacturing, but also form a huge industrial chain. China's embedded systems have developed at a slow pace - although it is not too late. Most of the embedded systems used in the products do not necessarily have high requirements for the chips. Generally, they are tens of nanometers to hundreds of nanometers, and even lower grades may be enough. Therefore, the technical difficulty is not great.

Product intelligence is a new major trend in the development of today's computing technology. The original intention of the invention of computing technology was for scientific calculation. Then it was developed to support the information processing and dissemination of various human business activities, namely business computing. Business computing coverage has been much larger than scientific computing. Since the 1990s, with the development of the Internet, QQ, WeChat, and facebook have begun to rise. Computing technology has infiltrated people's social life. This has greatly promoted the development of social computing, and the application coverage of computing technology has further expanded. Now, computing technology has begun to penetrate into various product areas and improve the level of product intelligence. With the number of smart products in the billions or even hundreds of billions, the coverage of product calculations can be said to be “far-reaching” and will certainly bring about tremendous changes to the entire IT industry. Therefore, the next hotspot of computing technology application is product calculation. All products must be intelligent to varying degrees, and calculations may be involved. This point has a lot to do with the rapid development of the Internet industry.

Figure | The development stage of computing technology applications

Today's smart products are not exactly the same as previously called functional requirements of embedded systems. Their main functions are embodied in three aspects. The first is sensing, and the product needs to be able to sense changes in external conditions or be able to integrate data within the product. The second is the calculation, including the operating system of the product itself, and the various application systems used by the product. For example, from data analysis to high-end computing—that is, artificial intelligence. The third is networking. With the development of the global Internet of Things, products may have the functions of fog computing, edge computing, and cloud computing. Therefore, the new generation of smart products is very different from the concept of embedded systems previously discussed.

Figure | Smart Products Everywhere

Smart equipment is the biggest difficulty

Equipment is the biggest difficulty in smart manufacturing. Production equipment is generally more complex, and the volume may not be large, and the industrial software used is often very complex. This makes the production cost very high, the market is very small, so there are not many companies that are willing or able to engage in intelligent equipment manufacturing. Moreover, due to the long development cycle of equipment, the risk of business operations is very high. In addition, the difficulty in equipment manufacturing is largely in soft equipment, ie, soft equipment represented by industrial software, including software tools such as CAD/CAE. Without soft equipment, there can be no "digital, networked, and intelligent." Withdrawing software, all the achievements of informatization no longer exist. Industrial software is primarily an industrial product and is often a high-end industrial product. This is the main difficulty for China to manufacture 2025, and the industry’s understanding of this point is still insufficient.

Process intelligence

The manufacturing industry in developed countries is already leading the way in the intelligent production equipment. In particular, Japan and Germany have basically monopolized the global market for major manufacturing manufacturing equipment. The next step in the development of smart manufacturing is to realize the intelligence of the process and complete the development of the “line” from the point of equipment to the process.

The most typical representative of process intelligence is the goal of Industry 4.0 and Industrial Internet. Industry 4.0 proposes that the information systems of enterprises should be integrated, including vertical integration and horizontal integration. Vertical integration is the intranet of the company mentioned in one of the series of "Three-Theory of Intelligent Manufacturing", and horizontal integration is the external network of the enterprise. Now, we must completely integrate the intranet and extranet to completely open the data.

Figure | Integration of Intranet and Extranet

In addition, the integrated system should be made into a Cyber-Physical-System (CPS). Cyber ​​here refers to a computer or computer network. In many modern enterprises, either the intranet or the extranet, it is still only an independent computer network or system, or has achieved initial integration. How to integrate with the physical entity of the enterprise and operate effectively is a question from a university. In a report in 2006, the National Science Foundation (NSF) of the United States pointed out that the existing system sciences (including systems engineering theory) developed in the industrial age have not been able to answer such questions well. They believe that how the physical entity of an enterprise and its embedded computers and network systems work together, efficiently, and accurately, and how to enhance the adaptability, autonomy, functionality, reliability, security, availability, and efficiency of such systems. It will develop into a new system engineering. It is the frontier proposition that the United States needs to focus on development. In fact, there are many research reports on CPS in the United States and they are very concerned about this topic.

The realization of process intelligence

The goal of Industry 4.0 or Industrial Internet is not only to connect internal networks and external networks, but also to become a CPS. Both can be expressed in a "5C" structure.

The bottom layer is the connection layer of wisdom, the second layer is the data conversion into information, the third layer is the Cyber ​​layer, is the enterprise's cloud computing data center. Here, the effective data obtained from the second layer needs to be compared with the corresponding expected values ​​in the enterprise computer system. The fourth layer is the cognitive layer. Based on the difference in comparison, the problem is found and the way to solve the problem. Therefore, this layer is actually a decision-making layer. The fifth layer is the configuration layer, which can be used to reconfigure or change people, objects, and computers through computer networks in accordance with decision-making requirements. Such a five-tier structure constitutes a standard feedback control system that can provide real-time feedback and control over the company's control objects, ie people (employees), machines, computer systems, and various physical entities. Such a feedback system, its corresponding technical support at each level, as shown in Figure 7. It is through the use of these most fashionable and advanced technologies that the Industrial Internet realizes the intelligent control of the entire business activities of the company.

Figure | "5C (Five Tier)" Architecture for Industrial Internet and Industry 4.0

According to this idea, Industry 4.0 and Industrial Internet completed the system architecture design in 2015 respectively. The reference architecture of the industrial Internet can clearly illustrate the elements of the system and the relationship between them and provide an open "Guide to the Design of Industrial Internet Systems." It should be emphasized that this is a guideline. It gives a direction for everyone to work together and go in the same direction rather than the standard.

This architecture design describes the internal and external three-tier structure of the industrial Internet system. From the edge layer, to the platform layer, to the enterprise layer, if we regard it as a sphere, the outside is the edge layer of the device, and the middle is the platform layer (Industrial Internet platform, mainly refers to this part. Of course there are also industries The trend of generalization of the Internet platform), the innermost layer is the enterprise layer. In the edge layer, the edge gateway is mainly used to collect a variety of data. After being sent to the platform layer, the platform layer processes and analyzes the data. After the analysis, it is delivered to the enterprise layer and sent to the enterprise application system. . Enterprises will make different analysis according to different applications, make judgments and decisions, and transmit the data back to the platform and edge layers until they are delivered to all departments and units within and outside the enterprise.

Figure | Internal and External Three-tier Structure of Industrial Internet Architecture

(Source: White Paper, Industrial Internet Alliance)

Obviously, data analysis and processing are extremely important in industrial Internet systems, including: acquisition of endpoint data, advanced data processing techniques for extracting information from data, analysis and calculation of various decision models, and output of system results. Among them, a large number of methods are used in computational science: modeling is needed, algorithms are needed, data is needed, and so on. Finally, decision data is generated. Of course, security, trustworthiness, privacy, etc. are also considered in detail in the structure.

Intelligent Manufacturing and Industrial Internet

Nowadays, many domestic discussions on the concept of industrial Internet platforms are discussed. The industrial Internet platform is an enterprise-centric platform, not a large so-called "industrial Internet platform" built in the entire industrial industry. The so-called platformization is the trend of development. It actually refers to the platformization of enterprises. Each large enterprise will have its own enterprise platform and will not move its own business to the platform of other companies. Boeing's platform will not be on the platform of AVIC, and Airbus's platform will not go to Boeing's platform. If we must say that there is a shared platform shared by industry and industry, then this platform is the global Internet of Things platform (IOT). It is not designed for which industry or for which department, but it is for all the world's banks. Industry, and even personal services, the global Internet of Things.

Industrial Internet platform is an ideal "process" intelligent platform. The idea is perfect, but the system is very complicated. In the process of implementation, there are still many unknowns, and the differences between enterprise platforms in different industrial categories are also significant. For example, the aviation industry's platform is almost impossible to use for PetroChina, and basically it has to be rebuilt. Therefore, each enterprise must proceed step by step from its own urgent needs and actual benefits, and must not follow blindly, especially considering that the current level of development of China's manufacturing industry and the level of informatization are still far from the international advanced level. The "process" of intelligence is still far away.

If all the resources and efforts of smart manufacturing are invested in the industrial Internet platform and the platform is understood as the platform of the industry, the development direction of smart manufacturing may be misjudged. The top priority is the intelligentization of our products and equipment. This is the focus of smart manufacturing in China today.

On the Three Aspects of Digital Transformation of Intelligent Manufacturing

Smart manufacturing is the main direction of China's manufacturing of 2025, while entrepreneurs are the main force of the frontal battlefield. How to realize the digital transformation of enterprises is the key to the success of smart manufacturing.

In January 2016, the World Economic Forum and Accenture co-published a white paper entitled "Digital Transformation in the Industry - Digital Enterprise". Among them, one of the most central ideas is that the role of information technology in economic and social development has risen from the supporting role of improving efficiency and labor productivity to the enabler of basic innovation and creation, and has evolved to support economic and social development. A major role for innovation and sustainable rapid development. Many international industry giants and scholars believe that digital transformation is one of the most important contents of the so-called "fourth industrial revolution."

For a long time, many companies have had chief information officer CIOs, but it is often difficult to play the "chief" role. Because, after all, information technology plays an auxiliary role in the enterprise. In general, not foreseeable entrepreneurs, it is difficult to understand what the purpose of large-scale informationization investment is, and where immediate results can be found. This is because the way information is expressed is different from that of general investment or the use of hard equipment (equipment). Many CIOs have the experience of “little daughter-in-law”. They feel that it is very difficult to convince the first person to attach importance to informatization, and that they have endless sweat. Now, with the development of informatization towards digital transformation, such an era is almost over. Talents engaged in IT business in the enterprise will gradually evolve into the protagonist of the enterprise; which company will fall behind in the era if it is not the IT protagonist, and will eventually be eliminated. The good day for the chief information officer CIO is coming. This is one of the accompanying phenomena that has brought about great changes.

Recognizing another perspective of the development stage of global informatization

Understanding the significance of digital transformation is related to a very important issue, which is to look at another perspective of the development stage of global informatization. From this perspective, the development of global informatization has gone through the following three different stages. In 2012, IBM's Saul J. Berman first proposed the concept of digital transformation; in 2016, Shahyan Khan in his article "Leadership in the Digital Age - Digitalization to Senior Management Leadership The Force's Impact Study points out that the process of human beings embracing digitalization can be divided into three stages: digitization of information, digitization of business, and digital transformation.

Figure | Three phases of the digital process

The first stage is the digitization of information. This stage addresses the digital issue of information itself, which is to take various forms of information, such as numbers, text, voice, pictures, videos, etc. The process of informationization begins with the digitization of information. Initially, data and characters were digitized; then, with the booming development of multimedia technology, digitization of pictures, voice, and video was gradually realized. The digitization of information is the starting point of informationization. Without the digitization of information, there would be no invention of an electronic digital computer. It would be impossible to use electronic digital computers to construct various information systems and to informatize business. There would be no economic and social progress brought about by today's information revolution. If, from around 1700, the German mathematician Gottfried Leibniz took the lead in proposing binary arithmetic, the digitalization of information has gone through more than 300 years. At present, the digitization of information continues to develop.

The second stage is the digitization of the business. The invention of the electronic digital computer in 1946 opened a new era of the contemporary information revolution and the development of informatization. In 1951, the United States Census Bureau purchased the world's first commercial computer for the processing of census data, and began the long road to digitalization of the world. The digitization of the business starts at the operation level of the company, and is most typical for accounting and statistical reporting systems. As described in the book “Modern System Analysis and Design” by Jeffrey A. Hoffer published in 2013, the developer of the first digital service information system in the United States is Electric Company (GE), which developed the first payroll system in 1954. Subsequently, business digitization gradually developed to management information systems and decision support systems. Since then, scientific computing, business computing, and social computing have gradually become the main application areas for digital computing. For more than 70 years, digital business has gone through three steps of digitization, networking, and intelligence; the three are not mutually exclusive, nor are you “singing me to the stage”, but “working hand in hand” to continuously improve the business. The level of digitization. The digitalization of the business has greatly improved the labor productivity and work efficiency of the entire society and has had a profound impact on the development of human economic and social society.

The third stage is digital transformation. Although the previous digitization of information and digitization of services have not ended and are still continuing to develop, the focus of the development of global informatization has begun to shift, and it has entered a new phase focusing on digital transformation. A new era of information technology development has come. .

Three aspects of digital transformation

The starting point for the digital transformation of the national economy or industry lies in the digital transformation of enterprises. A company in a traditional industry has become a digital enterprise through digital transformation. It mainly includes the following three important aspects.

First, it is the transformation of the business model (or business model) into a digital business model. This is the most basic and core essence of the digital transformation. Entrepreneurs must realize that the business model that has successfully operated in the past decades has been or will be destroyed by digital innovation and will not be effective forever. If companies do not make up their mind to “self-destruct and reborn,” discard or transform the original non-digital business model, and strive to create a flexible, digital business model that adapts to the digital age, it will surely fail in the future competition.数字业务模式，是一个数据密集和信息技术密集的业务模式，这是智能制造所呈现的全新特征，企业家无可回避。如果一家机床生产厂在转型前后都是只卖机床的，那么即使生产系统完全智能化了，由于业务模式没有变，那么仍然未能完成数字转型。

第二，是运行模式（Operational Model）的转型，即转型为数字运行模式（Digital Operation Model）。企业必须重新定义其基于计算机和网络的运行模式，清晰地描绘业务功能、流程、与组织架构之间的关系，在数字化、网络化、智能化、自动化的基础上，实现企业的战略和最终目标。就此而言，工业互联网和德国工业4.0将是数字企业运行模式的典型代表。

第三，是核心人才与技能（Digital Talent and Skills）的转型，数字人才与技能，将成为企业的核心技能。在数字转型的过程中，企业的技术专长和人才结构将发生深刻的变化。各种数字技术，包括建模与仿真、信息网络、人工智能、网络安全等技术，将要成为企业数字人才和技能的核心，企业的人才结构将发生深刻变化，信息化人才将占据特别重要的地位。而要实现这个转型，企业的领导层必须首先进入数字时代。德国工业4.0平台为了辅助中小企业的数字转型，在人才转型方面花了非常大的精力，提供了各种指导手册（如《数字人才转型指南》）和详细的案例。

值得注意的是，数字化转型（Digitalization Transformation）与数字转型（Digital Transformation）是非常不同的两个概念。前者强调的只是一个单位的运行模式的转型，并没有改变企业的业务模式；而后者强调的则是一个单位的业务模式的转型。从上面所述的、企业实现数字转型的三个方面不难看出，前者只是后者的内涵之一。

目前，网上有相当多的文章将数字化转型与数字转型混为一谈，混淆了概念，值得大家关注。二者虽然只差一个字，但却是一个重大的概念上的差异。如果当前企业关注的还只是数字化转型的话，实际上还是把重点聚焦在了企业的运行模式上，与以前推进的企业信息化并无差异。如此，企业忽视了业务模式转型的重要性，有可能导致一个重大的方向性偏差，延误了企业转型的战略机遇。

我国一些优秀的企业，近年来实际上都非常重视自身的数字转型。华为的数字转型启动就很早，其研发和生产的主要产品，从原来的通讯设备扩展至智能手机，就是一个重大的转型。2010年9月，华为生产了中国电信首批推出的天翼3G智能手机C8500，实现了由CT向IT+CT的转型。2017年，华为的手机收入为2300亿，已经占其业务总收入的1/3强。现在，华为也不仅是手机生产商，同时还生产自己的IT、芯片和软件产品。华为的软件队伍在6万人以上，成为中国少有的、拥有庞大的软件人才的企业，也是一个全数字的企业。

原来以空调产品引领行业的格力集团，也开始向智能装备制造转型。2010年，格力就向上游发展，切入模具制造。2016年3月，格力在武汉市蔡甸区投资50亿元，建设“格力智能装备制造业产业园”，主要从事精密模具、高端数控机床、智能自动化设备、大型商用空调、空调压缩机等产品的研发、生产和销售，从空调设备制造向智能装备制造转型的目标非常明确。这与德国许多优秀的企业，大力向上游装备产品进军以确保产品竞争力的思路，是非常一致的。同样是做消费电器和空调的美的集团，也在向机器人和工业自动化系统转型。美的收购了德国最大的一家机器人公司Kuka，一时惊动德国朝野上下。海尔集团也建设了面向全社会的孵化转型平台，实现用户的全流程最佳交互、交易和交付体验；其重点开发的COSMOPlat智能制造云平台，实现制造的数字化、柔性化、智能化，力图从传统家电产品制造向全社会孵化创客平台转型。

中国本土企业努力实现数字转型的例子还很多。显然，很多企业，特别是大企业，已经感觉到了当今世界正在发生的这个意义深远的变化：只有进行数字转型，企业才能有明媚的未来。

最后，值得一提的是，企业业务模式的数字转型，也顺应了当前全球物联网发展的大势。智能制造要求企业向数字化、网络化、智能化转型，实际上推动了企业产品智能化和智能产品的发展。只有智能化的产品才能够接入全球物联网，进入正在扑面而来的全球物联网时代。否则，产品和企业就有可能被边缘化、被淘汰。产品智能化和智能产品的发展，无疑将推动企业和产业的数字转型，特别是业务模式的转型，从而在最大程度上推进全社会数字经济的发展，推动国家的经济和社会的数字转型。

USB Flash Disk

USB 2.0 3.0 Flash Pen Drives FLASH Memory Pendrive USB Stick

1.What is the write speed ?
our USB 2.0 flash drive write speed is 5M/S - 10M/S or you will lucky to get 11M+.

Different device and different platform will affect a lot on the speed testing.
if you want to save 1GB film in our USB flash drive,that you need the time is 2 mins,it save your time.

2.Why the USB flash drive real capacity is not correct capacity?
Flash memory vendors are using decimal arithmetic:1MB = 1000KB,1G = 1000MB
calculated, the operating system using binary arithmetic:1MB = 1024KB,1GB = 1024MB;
so there are some differences between display capacity and nominal capacity of flash memory product
About capacity:
4GB=approximately 3.5GB-3.7GB
8GB=approximately 7.4GB-7.8GB
16GB=approximately 14GB-15GB
32GB=approximately 28GB-30GB
64GB=approximately 58GB-59GB
128GB=approximately 115GB-120GB

3.Note for the delivery (Please read before ordering ):
Value is less than 15$ Mode of transport = China Post, E-Packet Plus & Alibaba 3C Economic Package
1.Every shipping mode is sent with a tracking number, but there are several Countries or Areas can only be tracked before leave China.
2.The shipping leadtime to most of the countries, normal is 15 - 45 working days( Russia and Brazil 30- 60 working days)
3. If your Confirmation Time is coming,and still not do receive the goods,please contact with us to extend the delivery date and extend the delivery date at yourside at the same time.
4. However, Please do trust us. You will get the package in time.
5. If your Items is not received in 60 days,we will 100% refund
6. Please do not open dispute within 60days,Thanks for your kind understanding.

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MICROBITS TECHNOLOGY LIMITED , https://www.hkmicrobits.com