Technology
Aveva
Industry
Chemical Manufacturing
Client
SABIC T&I
Country
KSA
Goals
Upgrade PI Server from 32-bit to 64-bit architecture
Migrate 10 years of historical PI data seamlessly
Modernize interface nodes across five plants
Implement PI Asset Framework and PI Buffering for enhanced reliability
Challenges
Obsolete PI Server platform limiting compatibility and support
Migrating extensive historical data without loss or disruption
Coordinating upgrades across multiple, distributed interface nodes
Minimizing downtime during migration and upgrade
Solutions
Installed 64-bit PI Server on high-performance new hardware
Upgraded system to PI 2015 version with enhanced features
Migrated all historical data intact to the new environment
Upgraded six interface nodes and implemented PI Buffering
Deployed PI Asset Framework on dedicated node for structured asset modeling
Results
Robust, modern 64-bit PI System infrastructure with full backward compatibility
Preserved data integrity ensuring continuous historical access
Improved interface performance and system reliability across plants
Enabled structured data organization and future analytics expansion
Future-proofed PI system supporting SABIC’s innovation and operations
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SABIC T&I PI System Migration and UpgradeIn 2016, EMI successfully executed a comprehensive migration and upgrade of the PI System at SABIC’s Technology and Innovation (T&I) Center located in Saudi Arabia. The existing system was running an outdated PI Server, which posed risks related to reliability, compatibility, and scalability. The project’s core objective was to modernize this critical data infrastructure by transitioning to a robust 64-bit architecture while ensuring uninterrupted access to historical data accumulated over a decade. |
This upgrade encompassed a full migration of ten years’ worth of historical PI data to the new environment without loss or corruption, guaranteeing continuity in long-term data analysis and reporting essential for R&D and operational activities. Additionally, EMI upgraded interface nodes spanning five separate plants, enhancing data collection efficiency and communication reliability. A key part of the project was implementing PI Asset Framework (AF), which introduced structured asset modeling capabilities to facilitate organized data representation and enable advanced analytics. To improve data resilience, PI Buffering was integrated to protect data integrity during network outages or communication interruptions.
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