USE CASE
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01
Data Collection & Integration
- Collect and integrate data scattered across multiple equipment and systems into a centralized platform
- Structure unstructured data based on equipment ID, process stage, and time
- Consolidate all data into a single repository to establish a unified data management framework
02
Data Structuring & Automated Transformation (ETL)
- Reinterpret unstructured data into process-oriented metrics and terminology
- Perform mapping, cleansing, and transformation through automated ETL pipelines
- Automatically reconfigure data into schemas and formats optimized for AI training
03
Data Storage & Management
- Store integrated data in a data warehouse architecture for fast and efficient querying
- Establish an enterprise-wide data governance framework based on metadata
- Ensure traceability, consistency, and integrity through inter-process data mapping
04
AI Integration & Visualization
- Enable real-time data connectivity with higher-level systems such as AI Hubs and Digital Twins
- Intuitively visualize processes, equipment, and KPIs through dashboards
- Implement a real-time operational framework that connects AI insights to control actions and alerts
Insight
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