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Quality and safety risk analysis of intelligent consumer products based on LLMs and KG
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Yuexiang Yang1, Xuewen Liu1, Xinyu Tu1, Huaicheng Zheng1, Yingcheng Xu**, 2
China Safety Science Journal | 2026, 36(4) : 271 - 280
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China Safety Science Journal | 2026, 36(4): 271-280
• Intelligent Safety Technology •
Quality and safety risk analysis of intelligent consumer products based on LLMs and KG
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Yuexiang Yang1, Xuewen Liu1, Xinyu Tu1, Huaicheng Zheng1, Yingcheng Xu**, 2
Affiliations
  • 1School of Management, China University of Mining and Technology-Beijing, Beijing 100083, China
  • 2China National Institute of Standardization, Beijing 100191, China
Published: 2026-04-28 doi: 10.16265/j.cnki.issn1003-3033.2026.04.1582
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To effectively identify and control quality and safety risk of intelligent consumer products, a KG for intelligent consumer product quality and safety risk was constructed based on LLMs. Complex network analysis methods were integrated to systematically analyze risk distribution characteristics and propagation mechanisms. Data on intelligent consumer products were collected through multiple channels; the quality and safety risk issues in product accident cases were sorted out. Based on safety theories and the system structure of intelligent products, a multi-level and extensible knowledge ontology for quality and safety risks was constructed. Under the constraints of this ontology, LLMs were utilized to achieve automated knowledge extraction, and a KG containing 16 611 nodes and 32 178 edges was constructed. The KG was mapped into a risk network. Based on complex network theory, centrality indicators of three key node types—hazard factors, accident injuries, and safety events—were calculated to identify critical nodes and propagation paths in risk transmission. The research results show that among various intelligent consumer products, intelligent home products account for the highest proportion of risk entities; physical hazards and information hazards are the main risk types; property damage and physical injury are the primary accident consequences. Typical direct propagation paths and cascading propagation paths can be identified by the risk network.

large language models(LLMs)  /  knowledge graphs(KG)  /  intelligent consumer products  /  quality and safety risk  /  complex network
Yuexiang Yang, Xuewen Liu, Xinyu Tu, Huaicheng Zheng, Yingcheng Xu. Quality and safety risk analysis of intelligent consumer products based on LLMs and KG[J]. China Safety Science Journal, 2026 , 36 (4) : 271 -280 . DOI: 10.16265/j.cnki.issn1003-3033.2026.04.1582
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2026.04.1582
  • Receive Date：2025-12-14
  • Online Date：2026-07-08
  • Published：2026-04-28
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  • Received：2025-12-14
  • Revised：2026-02-24
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    1School of Management, China University of Mining and Technology-Beijing, Beijing 100083, China
    2China National Institute of Standardization, Beijing 100191, China
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https://castjournals.cast.org.cn/joweb/zgaqkxxb/EN/10.16265/j.cnki.issn1003-3033.2026.04.1582
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