Injection molding is the most widely used process for manufacturing polymeric products. As a result of the widespread applications of polymeric components in the electrical, electronic, and automotive industries, the quality of injection molded products and molding processes demands a more stringent specification. At the same time, rapidly changing customer needs in the competitive business environment have led to an urgent need for efficient polymeric product engineering to support the launch of successful products.

Intelligent manufacturing, a hot topic of the computer-related technologies sector, has also been talked about quite a bit in the polymer injection molding industry in recent years. Applying intelligent techniques to address challenging issues in injection molding has become a fast-growing and promising multidisciplinary research area. Intelligent injection molding makes it possible to sense, learn, analyze, and make decisions in all aspects of the polymer molding process. Therefore, it shortens product development cycles, improves the product quality and production efficiency, enables economical energy usage, and meets the growing demand for individualized products.

Intelligent technologies are widely accepted by the polymer industry now. However, existing research is still relatively fragmented, and there is still a lack of systematic perspectives and in-depth discussions. This special issue aims to explore recent developments in the field of intelligent technologies for polymer injection molding. Both original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Knowledge-based polymer product design and application
• Simulation and optimization for polymer injection molding
• Online monitoring during polymer processing
• Data mining and analysis from manufacturing and processing
• High-precision control for injection molding machine
• Economic and energy-saving polymer processing technologies
• High-efficient measurement of polymeric product
• Predictive maintenance techniques for polymer manufacturing equipment