Technical pathways for collective intelligence-driven collaborative design in custom furniture

To establish a collaborative design methodology based on swarm intelligence theory, and to overcome the limitations of traditional linear design models. By leveraging intelligent technologies, it seeks to achieve exponential improvements in design efficiency and promote the digital transformation and value chain restructuring of the custom furniture industry, with a focus on custom wardrobes.

A progressive research approach of “theoretical modeling, system construction, and empirical validation” is adopted, concentrating on custom wardrobe application scenarios. A three-layer collaborative architecture based on swarm intelligence is established. The design tasks are decomposed into three core modules: 1) user data acquisition and demand visualization module; 2) design knowledge function module; and 3) user collaborative design automatic generation module.

The swarm intelligence collaborative design system effectively addresses the contradiction between processing massive personalized design demands and delivering efficient service supply, confirming the feasibility of empowering the digital transformation of traditional manufacturing through intelligent technologies. The layered and decoupled architecture successfully achieves the integrated innovation of three key technologies: structured design knowledge (knowledge graph), intelligent demand analysis (deep learning), and automated solution generation (GAN algorithm).

At the theoretical level, a “demand-knowledge-solution” ternary collaborative model is proposed, expanding the application paradigm of swarm intelligence theory in the field of industrial design. At the practical level, the modular technical architecture developed for custom wardrobes offers a reusable solution for the industry's digital transformation. This design provides a new technological pathway for the intelligent upgrading of the home furnishing industry. To further promote industrial collaboration towards a higher dimension, efforts should focus on constructing cross-enterprise collaborative ecosystems and innovating cloud-based intelligent service models.