Hyperchain Technology’s AI-Powered Foundry Quality Management Platform was selected as a representative industrial AI use case at the World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance 2026, held in Shanghai from July 17 to 20.
WAIC 2026 was the largest and most internationally influential edition of the conference to date. Chinese President Xi Jinping attended the opening ceremony and delivered a keynote address.
The platform was recognized during the conference’s industry AI forum for its application of data governance, AI-ready datasets and intelligent agents in complex manufacturing environments.
Improving Quality Management Across Foundry Operations
Foundry manufacturing involves multiple interconnected processes, each generating large volumes of production and quality data. Fragmented data systems, inconsistent standards, limited cross-process traceability and delayed responses to quality issues can make it difficult for manufacturers to identify defects and determine their root causes.
Hyperchain’s platform addresses these challenges by integrating data management, AI-powered analysis and operational workflows into a unified quality management system.
The platform consolidates quality data from across the production process, standardizes data definitions and builds traceable relationships between materials, production parameters, equipment conditions and inspection results.
It applies foundation models, domain-specific models and AI agents to support:
- Real-time monitoring of critical quality indicators
- Automated detection of process anomalies
- Root-cause analysis of product defects
- Early warnings and coordinated issue resolution
- Closed-loop tracking of corrective actions
A quality knowledge graph also structures historical defects, production incidents and resolution methods, allowing accumulated operational knowledge to be reused in future analysis and decision-making.
Deployed Across Key Foundry Processes
The platform has been deployed at Shanxi Huaxiang Group Co., Ltd., covering key foundry processes including melting, pouring, molding, sand preparation and machining.
By connecting production data across these processes, the platform enables real-time quality monitoring, automated anomaly alerts and closed-loop resolution of quality issues.
Following implementation, the company’s defect escape rate decreased by more than 80%, while product yield increased by over 8%. These results demonstrate the platform’s ability to deliver measurable quality improvements in complex industrial production environments.
