The rapid development of new generation information technology and its deep integration with manufacturing technology are triggering major changes in manufacturing models, manufacturing processes, manufacturing methods and ecosystems. Intelligent manufacturing is undoubtedly a hot topic in industry, academia and education.
Intelligent manufacturing is the general term for advanced manufacturing processes, systems and models in today’s era, with lean manufacturing system as the The basis is to achieve optimal quality, cost and delivery time through informatization, automation and intelligence in the entire life cycle of design, supply chain, manufacturing, quality control, sales and service.
But the concept is easy to explain but difficult to implement. For small and medium-sized enterprises, smart manufacturing still has a long way to go and should be treated rationally.
The purpose of intelligent manufacturing
If you understand smart manufacturing as the application of a lot of technical means such as machine substitution, industrial software, sensors, etc., you are putting the cart before the horse. The purpose of intelligent manufacturing is neither the manufacturing process itself nor the application of “intelligent” means. Its core purpose can only be to improve manufacturing efficiency and effectively participate in industry competition in terms of efficiency, cost, and quality. This is the “king way” of intelligent manufacturing, and information technology is only a matter of “skills”.
For manufacturing, robots and artificial intelligence are just blown and floating bubbles, and they are all fake tricks used by IT manufacturers to sell powerful pills. Therefore, small and medium-sized enterprises need to think calmly in the process of embracing intelligent manufacturing, and not fall into the trend of blindly following the trend of others.
Is the enterprise suitable for intelligent manufacturing?
Smart manufacturing needs to match the nature of the industry. For process industries, smart manufacturing has been successfully applied due to its short intermediate production links and high degree of automation, and the risks are also low.
But for most discrete manufacturing industries, the manufacturing systems are complex. For example, in traditional machinery manufacturing, parts processing, equipment manufacturing industries, etc., their production forms are mostly relatively independent workshops, processes and machine tools, and connected production is weak. The process is complex, the production chain is long, and personnel skills are highly dependent, making it impossible to completely replace people with machines.
From the perspective of enterprise scale, many small and medium-sized enterprises have more than 100 employees. The enterprise’s CNC equipment has not yet been fully popularized, the network implementation at the production site is not perfect, and the ERP software has not been installed or applied. The effect is average, the basic data is inaccurate, there is a lack of informatization talents, and the supporting management mechanism cannot keep up. Talking about industrial cloud and big data at this time is undoubtedly too high-spirited and only a small gain.
Whether the investment cost can be afforded ?
Zhu Hai, President of Schneider Electric China, said: “Many people think that smart manufacturing means buying a lot of automation equipment, introducing robots, and automating for the sake of automation.”
If smart manufacturing is just a stack of physical equipment, it will definitely not do well; if smart manufacturing is just about extracting government subsidies, it will be even more meaningless.
Because of the high investment in intelligent manufacturing, we must adhere to a problem orientation, conduct full demonstrations, and have clear goals: What is the purpose of construction? What practical problems will be solved after investment? Are the costs of equipment, software and labor investment controllable? How much does subsequent maintenance cost? Is the input-output benefit cost-effective?
Under the impulse of enterprises, many high-end intelligent manufacturing software and hardware systems are applied, which are often noisy for a while, but then fall silent. However, we must know that small and medium-sized enterprises do not have sufficient financial resources and no government subsidies, so this sunk cost may be unbearable.
Is there a cultural foundation for implementation?
Culture is composed of a series of systems and working habits within an enterprise, and is reflected in the way of thinking and behavior of all employees. Li Peigen, an academician of the Chinese Academy of Engineering, believes that whether it is an enterprise or a government, we cannot only focus on the concept of intelligent manufacturing, let alone ignore people.
People are the carrier of corporate culture. The role of people in the application process of intelligent manufacturing systems is a blind spot that domestic enterprises ignore. When we choose automation equipment, do we consider the matching of personnel’s technical capabilities? Why do we not see an improvement in efficiency after implementing ERP and MES? We chase hot spots and use the APS advanced scheduling system to improve order delivery rates. Why is the improvement limited? Have we seriously thought about the relationship between information systems and people?
In the context of large-scale customized intelligent manufacturing, when companies put a large number of intelligent equipment and software into the field, the actual This has changed the traditional resource pattern of “man, machine, material, law, and environment”. Companies applying intelligent manufacturing will need to build a new human-machine collaboration mechanism in the future. Compared with the traditional manufacturing model, this new mechanism has several obvious changes:
Decision-making mechanism��Change
From human decision-making to information-based tool-assisted decision-making, the balance between human and data decision-making is difficult.
Changes in collaboration mechanisms
“People-people” interaction, Changes to the “human-machine” and “machine-machine” interaction methods, production site collaborative communication methods, and information transmission efficiency have brought about changes in the original organizational form and business processes.
Changes at the execution level
Accept orders from others and change People accept partial or even complete command from the system (digital). The role of people is weakened in some aspects, such as product design, production planning, and task dispatch; but it is strengthened in some aspects, such as analysis, decision-making, scheduling, organization, and management. . How to evaluate people’s performance, evaluate the efficiency of equipment and machines, and improve the execution of production site resources poses many new organizational ethics challenges.
Frankly speaking, the quality of manufacturing workers and managers in most small and medium-sized enterprises in China is still at a relatively early stage. Whether it is sense of responsibility, knowledge reserve, skill level, or mastery of information tools, they will still be long-term challenges. At the same time, organizational structure, management processes, salary models, and management innovation must also keep pace with the pace of smart manufacturing. Faced with the changes brought about by smart manufacturing, it is obvious that many small and medium-sized enterprises are not ready yet.
Intelligent manufacturing is both a direction and a process. The informatization of small and medium-sized enterprises has just started, so they cannot blindly embrace smart manufacturing and expect to achieve success overnight. We should adhere to manufacturing as the core and move closer to intelligence in stages by sectors. </p
