Sustainable packaging user-centered design employing CycleGAN and deep learning

An innovative approach was pursued for sustainable packaging design using Cycle Generative Adversarial Networks (CycleGANs), tailored for wood packaging engraving. The methodology includes four phases: user participatory design, assembly scheme design, detailed Finite Element Analysis (FEA) optimization, and computer numerical control (CNC) engraving production. Each phase targets sustainability from design to final product, minimizing environmental impact and economic costs. Emphasizing early user participation helps adapt designs to user needs and environmental standards. Innovations such as real-time updates of packaging patterns via cloud-based iterations and an FEA optimization system enhance durability and aesthetics. This approach improves the environmental footprint and recyclability of conventional wood packaging. The research aims to shift perceptions in the packaging industry towards more sustainable practices, showcasing the practical applications of advanced digital tools in traditional manufacturing. It offers a scalable model for integrating sustainability into packaging design, providing valuable insights and inspiring future innovations in environmentally friendly practices across the industry.