**What is Smart Manufacturing Technology?**
Intelligent manufacturing technology involves the use of computer simulations to replicate the intelligent activities of experts in the manufacturing industry, such as analysis, judgment, reasoning, conception, and decision-making. These intelligent activities are integrated with smart machines across the applications and subsystems of an entire manufacturing enterprise, including management decisions, procurement, product design, production planning, manufacturing assembly, quality assurance, and marketing. This integration aims to achieve a high level of flexibility and integration in the entire manufacturing process, thereby replacing or extending the mental work of human experts in the manufacturing environment. It also facilitates the collection, storage, improvement, sharing, inheritance, and development of expert knowledge, making it an advanced manufacturing technology that significantly improves production efficiency.
**Challenges in Intelligent Manufacturing Technology**
First, ensuring the real-time, accuracy, and comprehensiveness of information systems (virtual world) for on-site production and operation systems (real world). Currently, two main methods are used for data collection at the production site: automated data collection and manual data collection. Automated data collection typically relies on equipment with good communication capabilities and various sensors. Manual data collection is often used as a supplement or alternative when automation is difficult or costly. However, due to the complexity of on-site conditions, manual data collection is widely used, leading to reduced real-time accuracy and difficulty in collecting field data due to cost constraints.
In terms of data acquisition, the Siemens factory is considered an ideal example. Sensors placed at key points along the production line and controllers with communication capabilities enable fast data acquisition, which is uploaded in real time to the information system, allowing accurate mapping from the real world to the virtual world. However, due to limitations in on-site equipment conditions, this success is hard to replicate in other factories. For instance, in the Mitsubishi Electric factory, poor communication capabilities of the equipment require manual data entry at each machine, affecting the accuracy and real-time nature of the data.
Second, converting massive data from the production site into effective suggestions for operational optimization. With the huge amount of data collected, it is challenging for both information system providers and factory operators to fully exploit its value, making it difficult to truly realize the leap from data to actionable insights. The lack of relevant mathematical models—such as equipment modeling and production operation modeling—is a major reason. Establishing these models requires deep understanding of equipment and business processes, as well as strong mathematical and abstract abilities, which are not easily achieved in the short term. This gap may explain the difference between the Siemens factory and true smart manufacturing. Without this link, it's impossible to form a closed-loop in production operations, limiting improvements in all aspects of production.
**Robotics and Intelligent Manufacturing Technology**
China’s manufacturing industry has gone through four stages, from the initial startup phase to growth, then to rise. Now, we are in a critical transitional phase. This stage brings more challenges and problems. While we have experienced everything from scratch to small-scale, the challenge lies in transforming from large to strong, which is a long-term mission requiring patience.
The development of China’s manufacturing industry is uneven. Some enterprises have reached higher levels of digitization and intelligence, while others remain in the manual operation stage. To drive innovation, product innovation must be prioritized, as it leads the way in manufacturing and robotics. Product innovation should be the core of any industry, as a single product can drive an entire sector. However, China’s overall innovation capability and key technologies still lag behind developed countries. Despite this, the government has emphasized this area by launching the "Made in China 2025" plan, aiming to elevate the country’s manufacturing to a national strategic level.
Smart manufacturing is not a one-step process but a gradual evolution. It begins with digitalization, which serves as the foundation. With the internet, resources can be dynamically stored and gradually become intelligent. The process of smart manufacturing is closely tied to product design, where the soul of the process lies. Design drives development, and smart design and manufacturing involve perception, analysis, decision-making, and execution. Therefore, smart manufacturing is a long-term goal, not just a conceptual stage.
Key features of smart manufacturing include using digital and intelligent means to transform customer needs, product development, production, and service into a whole line. Another important feature is the integration of internal lines—design, production, logistics, and marketing. Smart manufacturing aims to connect these lines, driving technological progress, improving competitiveness, and bringing real benefits to enterprises.
The core of smart manufacturing lies in product intelligence. As people’s demands for products increase, adding intelligence to a product can significantly enhance its competitiveness. Product innovation is therefore crucial. Without it, discussions about smart manufacturing remain theoretical. Innovation should focus on making the product smarter, faster, and more convenient. Some innovations involve adding sensors and algorithms to equipment, enabling autonomy, interaction, and communication. This approach can help find the right path for market-oriented product innovation.
Developing smart equipment is another challenge. Many foreign companies have excelled in this area over decades, focusing on precision and detail. China’s smart equipment market has potential, especially in high-end sectors. However, achieving this requires extensive integration, testing, and refinement. The journey toward smart equipment will be long and demanding.
Today, many digital workshops and smart factories are being implemented successfully. A digital workshop collects real-time data, allowing for efficient management. However, the next step is to make the entire factory smart. Larger factories may find this easier, while smaller ones face more difficulties.
**Core Technologies of Smart Manufacturing**
The core of smart manufacturing includes digital manufacturing technology, sensing technology, and robotics. Digital manufacturing requires models and guidelines for product design, innovation, and numerical control, forming the basis of smart manufacturing. Sensing technology involves using various sensors to gather information, supporting flexible configuration and dynamic adaptation. Robotics plays a vital role, especially in automotive and emerging fields like elderly care and space exploration. However, current robots have limited perception and operate mainly in structured environments. Human-robot collaboration is still in early stages, and future robots must evolve to interact naturally with humans and adapt to complex environments.
**Manufacturing Thinking**
Germany’s Fraunhofer Institute provides a model for focused research on key technologies, making them accessible to enterprises. This approach is supported by government funding, with projects involving collaboration between academia and industry. Such models highlight the importance of bridging the gap between academic research and practical application. In China, initiatives like the Wuxi Research Institute aim to accelerate the development of smart manufacturing by integrating research and practice.
Looking ahead, the development of smart manufacturing will require interdisciplinary collaboration, combining information technology, materials science, mechanics, and physics. It is essential to strengthen basic research, expand new growth areas, and train high-level talent. International cooperation will also play a crucial role in advancing China’s manufacturing capabilities.
In conclusion, smart manufacturing is a long-term pursuit that demands adaptability, self-discipline, and a focus on national needs. By leveraging digitalization and innovation, China can move from a manufacturing giant to a manufacturing power, contributing to global industrial transformation.
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