AIGC-assisted Product Design Method Based on Prompt Word Optimization

WU Jing; WANG Shence; NIU Hongsu

doi:10.19554/j.cnki.1001-3563.2025.16.016

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (16) : 186-201. DOI: 10.19554/j.cnki.1001-3563.2025.16.016

Industrial Design

AIGC-assisted Product Design Method Based on Prompt Word Optimization

WU Jing, WANG Shence^*, NIU Hongsu

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Abstract

In response to the challenges of formalizing requirements, unstable solution quality, and incomplete evaluation standards in product design with AIGC technology, the work aims to explore the development of an Artificial Intelligence Generated Content (AIGC)-assisted design method for products. A Prompt-Optimized AIGC Design (POA) framework was constructed, which enhanced the quality of AIGC-assisted design through collaborative iteration across requirement analysis, concept generation, and solution evaluation. Firstly, the multi-source data analysis based on Principal Component Analysis (PCA) was used to formalize design requirements and extract key principal components such as appearance features and dynamic performance. Secondly, a hierarchical prompt word structure ("basic description + functional constraints + style definition") was constructed based on the Contrastive Language-Image Pretraining (CLIP) model, which optimized the generated quality through directional optimization and structural reconstruction. Finally, an improved AHM-TOPSIS multi-criteria decision-making method was applied to establish a multi-dimensional quantitative evaluation system that included ergonomics, material selection, and other factors. With the handheld rotary tiller design as a case study, the results showed that compared to the pure AIGC method, the proposed POA method significantly improved requirement analysis, concept generation, and iterative optimization, while also reducing the overall design cycle. Furthermore, the innovation of solutions and user satisfaction were enhanced. The proposed Prompt-Optimized AIGC Design method standardizes the application of AIGC technology in product design through structured requirement expression, solution optimization, and multi-criteria decision-making evaluation, providing a new theoretical framework and technical pathway for the AI-assisted design.

Key words

Artificial Intelligence Generated Content (AIGC) / Prompt Word Optimization (PWO) / Contrastive Language-Image Pretraining (CLIP) / handheld rotary tiller (HRT)

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WU Jing, WANG Shence, NIU Hongsu. AIGC-assisted Product Design Method Based on Prompt Word Optimization[J]. Packaging Engineering. 2025, 46(16): 186-201 https://doi.org/10.19554/j.cnki.1001-3563.2025.16.016

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