Ceramic Process Optimization and Automation Design Based on CAD and Reinforcement Learning

Abstract

As modern science and technology progress swiftly and market competition intensifies, conventional ceramic manufacturing techniques encounter numerous challenges. By introducing the overview of computer-aided design (CAD) technology and the basic principle of reinforcement learning (RL), this article analyzes the combination of them in the ceramic industry and puts forward a ceramic process optimization method based on CAD and RL. This method accurately extracts the design features and process features of ceramic products and combines the RL algorithm to automatically explore and optimize process parameters, thus realizing efficient optimization and automatic design of ceramic processes. As a key link in connection design and optimization, the importance of feature detection of ceramic products has been fully reflected in this study. The research results show that this method can significantly improve the quality and production efficiency of ceramic products and provide a new direction for the innovation, development, transformation, and upgrading of the ceramic industry. By combining the accurate modelling of CAD technology with the intelligent optimization of RL, the ceramic industry is expected to realize the automation and intelligence of the whole process of design, manufacturing, and optimization, and further enhance the market competitiveness.