Built upon the GloryIGI industrial large model and integrating agentic AI with diverse capabilities, LOFA implements intelligent manufacturing upgrade scenarios across industrial applications to serve as the fab's smart control hub and unified system entry point. It achieves process automation and AI-driven recognition/parsing, allowing virtual assistants to replace or assist across multiple roles, transform production workflows, reduce costs, improve efficiency, and elevate fab decision-making and workforce productivity.

Relying on industrial large models and knowledge graphs, it builds an enterprise-exclusive smart assistant system. GloryIGI captures and consolidates industry-specific and proprietary enterprise knowledge to support intelligent Q&A, analysis, and decision-making assistance across high-value scenarios such as R&D, production, equipment, and management, driving continuous intelligent upgrades in industrial scenarios.

Based on multimodal information collection including images, video, and voice, combined with AI agents and reasoning large models, PMS automatically understands inspeaction and fault scenarios, matches maintenance and repair solutions from the equipment knowledge base, and generates actionable operational guidelines to achieve an intelligent and process-driven closed loop for equipment inspection, diagnosis, and maintenance.

Combining AI and large model capabilities, YMS automatically analyzes process, inspection, and quality data, identifies correlation between yield and defects, enables anomaly early warning, root-cause analysis, knowledge accumulation, and decision support, building an intelligent closed loop for continuous quality improvement.

BDP uniformly integrates data from MES, equipment, inspection, and business systems, relying on big data and intelligent analytics technologies to perform data governance, feature modeling, and metric analysis, supporting the rapid construction and stable operation of diverse AI applications such as quality, yield, equipment, and operations.