Research Progress and Prospects on Artificial Intelligence in the Field of Flat Glass Production: Technological Integration and Industrial Transformation

Flat glass as an important foundational material in various industries such as construction, automotive, and electronics has a significant importance in promoting the development of related industries through its production efficiency and product quality. With the development of the global economy and the continuous growth of demand for flat glass in various applications, the size of the global flat glass market is still expanding. However, the conventional flat glass industry faces some challenges in production, testing, logistics, and other aspects due to its low production efficiency, unstable product quality, high energy consumption, and high logistics costs. The rapid development of artificial intelligence technology brings some opportunities for transformation to the flat glass industry. It can play an important role in material and performance prediction, intelligent control of production processes, precise quality inspection, and efficient logistics management, effectively improving production efficiency, product quality, and market competitiveness, reducing production costs and energy consumption and promoting the sustainable development of the industry.

This review mainly discusses the current development status and existing problems of artificial intelligence in the field of flat glass production, revealing the practical effects and challenges faced by artificial intelligence technology in promoting the intelligent development of the flat glass industry. In terms of component design and performance prediction, machine learning algorithms establish accurate prediction models via mining inherent patterns in a large amount of experimental data. For instance, the research and development cycle of new materials shortens and research and development costs reduce via combining neural networks and genetic algorithms to design new glass materials with specific optical properties and using random forest models to design components for lightweight and low expansion curtain wall glass. In terms of production process control, artificial intelligence technology plays an important role in core processes such as raw material processing, melting, forming, annealing, defect detection, cutting and sorting. Fuzzy modeling and genetic algorithm based on layered architecture are used for furnace operation optimization, and computer vision models are used for float glass melting furnace liquid level detection and control, thus improving production efficiency and product quality. In terms of identifying and diagnosing product defects, deep learning technology improves recognition accuracy and practicality through innovative model architecture, multimodal data fusion, and optimized computational efficiency. Object detection and segmentation models based on convolutional neural networks are widely used in glass defect detection. In terms of transportation, warehousing, and scheduling of flat glass raw materials, intelligent warehousing management systems and intelligent scheduling systems are gradually applied to flat glass enterprises, effectively improving the efficiency and accuracy of warehousing management and reducing transportation costs.

Although artificial intelligence has a great potential in the field of flat glass, there are still some technical challenges and application bottlenecks, such as data quality, process complexity, dependence on professional knowledge, and talent shortage. In the future, it is necessary for the enhanced practicality and reliability of artificial intelligence technology in the complete production chain of flat glass to further strengthen the application research of artificial intelligence technology in practical scenarios such as formula adjustment, performance prediction, production process control, defect detection, logistics and warehousing of flat glass, solve the problems encountered in the process of technology implementation, and improve the connectivity of data and adjustment solutions between various production links. Meanwhile, it is important for the increasing application of artificial intelligence in the field of flat glass to establish unified industry standards and specifications. In the future, artificial intelligence will develop in the field of flat glass towards technological breakthroughs and innovation, as well as the expansion and deepening of application scenarios, thus promoting the integration of technological innovation and industrial transformation in the flat glass industry.