Chemical Plant Data Transfer Tagging for Secure Cloud Integration
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Solution Overview
Problem
Chemical plants face challenges in leveraging data for increased production efficiency due to high security standards that restrict the migration of embedded control systems to cloud computing, leading to latency and availability issues.
Innovation Solution
A system with multiple processing layers, including a secure network layer and an external processing layer, that uses a transfer tag to securely and efficiently transfer process or asset specific data and applications, allowing for seamless integration with external systems while maintaining high security standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If embedded control systems are migrated to cloud computing, then data processing efficiency and production efficiency are improved, but security standards are compromised and latency issues occur
Solution Approach 1:
The system is divided into multiple processing layers: a secure network processing layer that handles real-time control data within the chemical plant's secure network, and an external processing layer that handles non-real-time data analysis in the cloud. This segmentation allows different security requirements to be met for different functions, enabling cloud computing benefits while maintaining security for critical operations.
Solution Approach 2:
A secure network processing layer acts as an intermediary between the embedded control systems and the external cloud computing resources. This intermediary layer processes and filters data before external transmission, ensuring that only non-critical data leaves the secure network while critical real-time control remains isolated, thus maintaining security standards while enabling cloud-based analytics.
2Productivity
If data is transferred to external systems, then data processing capability is improved, but data security and access restrictions are compromised
Solution Approach 1:
Different security levels are applied to different processing layers. The secure network processing layer maintains strict security controls for real-time data, while the external processing layer handles less sensitive aggregated data. This local quality approach allows data processing capabilities to be extended externally without compromising the security of critical data remains in the secure network.
3Adaptability or versatility
If cloud computing is implemented, then scalability is improved, but latency and availability issues worsen
Solution Approach 1:
The system adds a spatial dimension to processing by distributing different types of processing across different locations and networks. Real-time control processing remains in the local secure network for low latency, while batch analytics and historical data processing are moved to external cloud resources for scalability. This dimensional separation resolves the latency-scalability tradeoff by assigning different functions to different dimensions of the system architecture.
Data Source
AI summary
A system (10) for monitoring and/or controlling one or more chemical plant(s) (12) including at least one processing layer (14, 16, 32, 34), wherein the at least one processing layer (14, 16, 32, 34) is associated with a secure network (20) and communicatively coupled to an interface (26) for providing process or asset specific data or process applications to an external processing layer (30), wherein the at least one processing layer (14, 16, 32, 34) is configured to add a transfer tag to the process or asset specific data or to the process application and to provide the process or asset specific data or the process application based on the transfer tag.


