The manufacturing industry is currently facing challenges such as labor shortages, declining productivity, business downsizing, and rising costs. As a result, there is a growing need to establish a system that enables efficient production with limited human resources. To address this, there is a strong demand for utilizing generative AI to automate and streamline the product design process. Therefore, this study aims to automate the CAD design process by utilizing generative AI technologies, which can significantly streamline design workflows and reduce human workload. Specifically, we aim to construct a model that can automatically generate 3D shapes based on input shape features. As a preliminary step toward achieving this goal, we are currently working on the construction of a network that generates a new point cloud, which retains the essential shape features of the training data, using Generative Adversarial Networks. The accuracy and practicality of the generated point clouds are discussed.
ISHIHARA et al. (Wed,) studied this question.