The turning point in the manufacturing industry has finally arrived. With the release of the "New Generation Artificial Intelligence Development Plan" by the State Council, China has officially sounded the alarm for its national AI strategy. According to CCID Consulting, the AI market in China is expected to surpass 43.9 billion yuan by 2019, with a compound annual growth rate of 22.8% over the next three years. As emerging applications like smart homes, AR, and facial payment mature, and as smart cities and intelligent manufacturing continue to evolve, the AI market is set to grow steadily.
Among these developments, the transformation of traditional manufacturing through smart technologies stands out. At the Baidu Yunzhi Summit 2017, Shougang Group, a representative of traditional steel companies, demonstrated how AI could be used to detect defects in steel plates. Within minutes, Baidu ABC's integrated machine learning system analyzed 10,000 images, identifying 9,714 flawless plates, along with 280 red spots, 3 folds, and 2 holes—achieving an accuracy rate exceeding 99.9%.
In September 2017, Ruan Guoping, general manager of Beijing Shougang Automation Information Technology Co., Ltd., highlighted that the main challenges in China’s steel industry include automation in quality control and production equipment. The company aims to make significant progress in intelligent identification and classification of steel products, improving efficiency and quality control.
Improving quality control through smart technologies is just the beginning of the intelligent manufacturing revolution. According to Wang Ping, a global managing partner at McKinsey, "Smart manufacturing technology will change the entire lifecycle of commercial products—from customer orders to after-sales service."
In the steel industry, smart technologies are already making a real impact. Li Wei, deputy general manager of Baosteel Engineering Technology Co., Ltd., explained that traditional methods couldn't monitor the state of high-temperature ladles, which affected efficiency, cost, energy consumption, and safety. Through collaboration with Baidu Cloud, Baosteel developed the Tiangong Intelligent IoT, which collects data on temperature and pressure, supplemented by thermal imaging. This allows for comprehensive analysis and prediction, enabling better decision-making in chemical production, equipment safety, and energy saving.
Beyond steel, smart technologies are also transforming other sectors. Shanghai Zhenhua Heavy Industry (ZPMC), a leader in port machinery, deployed automated systems at Qingdao Port, including seven shore cranes, 20 automated orbital cranes, and 38 L-AGVs. The terminal now operates 40 natural tanks per hour, 30% faster than traditional terminals, with 85% fewer staff.
In the energy sector, companies like Concord New Energy and Vision Energy use Microsoft Azure Cloud to collect and analyze sensor data, optimizing performance and monitoring hardware. Bao Jiafeng, vice president of Microsoft Greater China, emphasized the importance of digital transformation.
However, many Chinese manufacturers still lag behind. According to Accenture, only 4% of Chinese manufacturing companies are "digital leaders," while 58% perform poorly in both digital input and operational performance. Digital transformation requires not just technology but also organizational change.
Wang Taiyong from Tianjin University noted that digital manufacturing involves using digital tools throughout the product lifecycle. Bao Jiafeng advised companies to start small, testing digitization in specific business modules before scaling up. “Digitization is a process that needs gradual adaptation,†he said.
Ultimately, the journey toward intelligent manufacturing is ongoing, requiring both technological innovation and cultural shifts within organizations.
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