Artificial Intelligence Techniques for Polymer Processing

Dear Colleagues,

The rapid evolution of artificial intelligence, the Internet of Things, and 5G technologies has accelerated the development of digital, intelligent, and unmanned manufacturing technologies. It is likely that future technology will be manufactured under an advanced network infrastructure through the deployment and integration of sensing and control technology combined with the integration of virtual and real artificial intelligence and machine learning to establish computation technology so that product design, manufacturing, equipment monitoring and maintenance, production scheduling, and process parameter optimization are integrated and flexible.

Machine learning is an important part of moving towards Industry 4.0. With the huge amount of information available, it is necessary to model manufacturing processes manually at their beginning and after completion. Such processes need to be self-trained by machine learning, so that the continuously input data can adjust the operating conditions more quickly. This is related to technologies such as real-time data pre-processing, feature extraction, and dynamic modification of new data with existing models. As for the application of polymer processing, design defects can be found in the virtual model using virtual and real integration systems to confirm the best time for machine maintenance and perform equipment maintenance in the virtual world. Related technologies include domain knowledge of manufacturing technology, sensing and communication technology, the Internet of Things, cloud computing, artificial intelligence, big data analysis, and digital reality technology.

The aim of this Special Issue is to present the latest research on “Artificial Techniques for Polymer Processing”. We invite researchers to contribute to this issue by submitting related articles and review papers.

Prof. Dr. Ming-Shyan Huang
Guest Editor

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