Linna Zhu, Ningyu Xiang
In the context of deep AI–design integration, traditional methods struggle to translate multi-source requirements into sustainable engineering solutions while balancing innovation with practicality. This study proposes AQTA, an intelligent design framework that integrates Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD), Theory of Inventive Problem Solving (TRIZ), and AI-Generated Content (AIGC) to enable sustainable product development. AQTA employs a four-stage closed-loop process: requirement analysis, contradiction resolution, solution generation, and validation. QFD and AHP quantify user and sustainability requirements to identify key contradictions, TRIZ resolves technical conflicts and stimulates innovative solutions, while AIGC generates eco-efficient visual concepts through prompt engineering. Multi-criteria decision-making supports evaluation and optimization based on environmental and economic indicators. Empirical studies demonstrate that AQTA significantly enhances innovation quality, design efficiency, and sustainability performance. The framework provides a replicable, hybrid ‘theory-driven + AI-generated’ methodology, which is validated through the case study of urban fire trucks, contributing to sustainable manufacturing practices in the intelligent era.