Manufacturing Should Gradually Move Towards Intelligent Manufacturing

[Introduction] From a technological perspective, intelligent manufacturing technology is a comprehensive technology formed by the interpenetration and interweaving of manufacturing technology, automation technology, systems engineering, and artificial intelligence. Its specific manifestations are numerous, including intelligent design, intelligent processing, robot operation, intelligent control, intelligent process planning, intelligent scheduling and management, intelligent logistics, intelligent assembly, intelligent inspection, intelligent maintenance and fault diagnosis, and new manufacturing models, among others.

It should be said that, like artificial intelligence, intelligent manufacturing is not a new concept. As early as the 1980s, during the peak of artificial intelligence, intelligent manufacturing also gained popularity.

However, due to limitations in bandwidth and communication networks at the time, coupled with the fact that the manufacturing industry itself focused more on product design and manufacturing processes, intelligent manufacturing projects in Europe, Japan, and other regions did not achieve the desired results.

Artificial intelligence (AI) encompasses a very broad range of technologies. Any stage in the entire intelligent lifecycle, employing any specific AI technology, can fall under the scope of intelligent manufacturing. Today, the manufacturing industry itself has expanded to include the entire lifecycle, encompassing product innovation and design, processing and manufacturing, management and marketing, after-sales service, and end-of-life disposal. Intelligent manufacturing faces rapid development and is highly anticipated.

It can be said that the advancement of information technology and the development of AI have provided a tremendous impetus for the development of intelligent manufacturing. Currently, neural networks have evolved to deep learning with over 152 layers, approaching human-level performance in areas such as image recognition and translation. AI is developing towards a hybrid intelligence model of "computer + human," with big data intelligence, cross-media intelligence, and numerous unmanned systems all bringing opportunities for the development of intelligent manufacturing.

In the future, the application of automation in knowledge-based work will be very promising. For example, intelligent sensing and cognition will be widely and deeply applied in manufacturing. Through various new sensors installed on assemblies, we can remotely monitor the health and operating status of equipment, achieving sensing. Furthermore, we can use big data and machine learning algorithms to detect equipment anomalies early, enabling timely maintenance and repair, and even "self-healing," achieving cognition. Currently, equipment monitoring systems composed of sensors, servers, and client devices have been implemented in my country's high-speed rail and some urban infrastructure projects.

Of course, intelligent manufacturing is not just about "high-end, large-scale, and sophisticated" applications; it can play a role in all levels of the manufacturing industry. In other words, intelligent manufacturing can also be "grounded" in everyday life; it's all around us.

Furthermore, the ultimate goal of intelligent manufacturing is industrialization, which depends on whether it brings benefits to enterprises and contributes to their sustainable development. Therefore, I suggest that the guiding principle for implementing intelligent manufacturing should be: enterprise-led, benefit-driven, overall planning, phased implementation, key breakthroughs, and innovative development.