Next-Generation Furniture Design The Convergence of AI and Digital Transformation

At a time when the design industry faces increasing complexities in the fields of aesthetics, functionality, ergonomics, spatial constraints, and diverse user preferences, traditional approaches are no longer sufficient to meet the needs for fast, accurate, and personalized design. Therefore, the convergence of artificial intelligence and digital transformation has opened new horizons for creating, evaluating, and optimizing furniture designs. In this research, first, the concept of complex relationships in furniture design is explained as a network of structural, functional, spatial, and human variables. Then, the application of Reinforcement Learning (RL) in layout optimization and automated decision-making in interior environments is examined. Furthermore, Graph Neural Networks (GNNs) are introduced as a tool for modeling the relationships between furniture components, space, and the user. On the other hand, generative ۳D models enable the rapid and creative generation of diverse forms and significantly increase the speed of the ideation and prototyping process. Alongside these, the role of interactive AI in enhancing human-machine collaboration, promoting creative decision-making, and facilitating the participatory design process is considered. The findings of this article show that the integration of these approaches can lead to increased efficiency, improved design quality, reduced development time, and the creation of a more flexible and intelligent experience in furniture design. Finally, it is emphasized that the new generation of furniture design is shaped not merely by automation, but based on the creative symbiosis of the designer and intelligent systems; an approach that will lead the future of the furniture industry towards deep personalization, data-driven design, and continuous innovation.

کلیدواژه ها:

Digital Transformation ، Reinforcement Learning ، Furniture ، Artificial Intelligence ، Decoration.