Chemical Plant Data Layering for Secure Cloud Monitoring
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Solution Overview
Problem
Chemical plants face challenges in leveraging data for increased production efficiency due to restrictive security standards, which hinder the migration of embedded control systems to cloud computing and big data analytics, limiting the integration of new technologies like IoT and cloud computing.
Innovation Solution
A distributed computing system with two processing layers, where the first layer is associated with the chemical plant and communicatively coupled to a second layer, allowing for seamless data access and cloud connectivity while adhering to high security standards, enabling contextualization and flexible handling of process applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If embedded control systems are migrated to cloud computing system, then data processing capability and production efficiency are improved, but security standards and system reliability are compromised
Solution Approach 1:
The system is divided into three distinct layers: embedded control layer (Level 1) for real-time control, cloud-based data processing layer (Level 3) for analytics, and intermediate communication layer (Level 2) for secure data transfer. This segmentation allows each layer to operate independently with appropriate security measures, enabling cloud migration without compromising overall system security.
Solution Approach 2:
An intermediate communication layer with firewalls and protocol converters acts as a mediator between the embedded control layer and cloud layer. This intermediary enables secure data exchange by filtering and transforming communications, allowing productivity improvement through cloud computing while maintaining security standards through controlled access points.
2Loss of information
If cloud computing system is implemented, then data analytics capability is improved, but system complexity and integration difficulty increase
Solution Approach 1:
The cloud-based data processing layer is designed as a universal platform that can handle multiple types of industrial data (process data, maintenance data, quality data) through standardized interfaces. This multi-functionality reduces system complexity by providing a single integrated solution rather than multiple specialized systems.
Solution Approach 2:
The system transforms data from various formats and protocols at the embedded control layer into standardized parameters suitable for cloud processing. By changing data parameters and representation formats through the intermediate layer, the system simplifies integration complexity while maximizing analytics capability.
3Adaptability or versatility
If data is transmitted to external network, then accessibility and scalability are improved, but security risks and access control difficulty increase
Solution Approach 1:
The system adds a new dimensional layer (cloud-based Level 3) above the traditional embedded control layer, enabling scalability and external accessibility without directly exposing the control layer to external networks. This dimensional change allows the system to scale horizontally through cloud resources while maintaining security boundaries.
Solution Approach 2:
Firewalls and secure communication protocols act as intermediaries that enable controlled access to the cloud layer from external networks. This intermediary approach allows scalability and accessibility improvements while filtering out security risks through multiple layers of protection and authentication mechanisms.
Data Source
AI summary
The disclosure relates to a system (10) for monitoring and/or controlling one or more chemical plant(s) (12), wherein the system (10) comprises a first processing layer (14) associated with the chemical plant (12) and communicatively coupled to a second processing layer (16), wherein the first processing layer (14) and the second processing layer (16) are configured in a secure network (18, 20), wherein the first processing layer (14) provides process or asset specific data (22) of the chemical plant (12) to the second processing layer (16), wherein the second processing layer (16) is configured to contextualize process or asset specific data to generate plant specific data and to provide plant specific data (24) of one or more chemical plant(s) (12) to an interface (26) to an external network.