Research on the Parametric Design and Application of Ceramic Modeling Based on Python
Zhenjie Wang, Longyao Xu, Jing Dai, Chengqian Zeng, Yu Zhong, Liyan Liu, Shuanghua Wang · Applied Sciences · 2025
In response to the growing diverse needs of the ceramic industry, this paper presents a creative approach employing the ErgoLAB human–machine environment synchronization platform to identify key parameters for ceramic shape parametric design. By collecting and analyzing multimodal data, including eye movements, electroencephalographic signals, and skin conductance, the study systematically determines the core factors influencing the user experience. Based on this, a Python (IronPython 2.7.9 (2.7.9.0) on NET 4.0.30319.42000 (64-bit))-based parametric design process is developed, covering parameter selection, shape generation, and model visualization. A model library of classic ceramic shapes is rapidly constructed, and ergonomic experiments further investigate the human–computer interaction mechanisms involved. The designs are optimized using fuzzy comprehensive evaluation for aesthetic appeal. Combined with 3D printing technology, a complete closed loop from design to manufacturing is achieved, verifying the manufacturability of the designs. This study not only deepens the understanding of ceramic shape parametric design but also offers strong support for the diverse development of the ceramic industry, providing valuable references for parametric design applications in other industrial fields.