Process Control Big Data Architecture for Unified Plant Data Access
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Solution Overview
Problem
Current process control systems face limitations in data management and analysis due to limited controller memory, communication bandwidth, and relational database capabilities, leading to inefficient data archiving, inaccurate troubleshooting, and cumbersome workflows, especially in batch process control systems where data silos create barriers for accessing and analyzing historical data.
Innovation Solution
A process control system big data network that collects and stores all data generated by process control systems using a unitary, logical data storage area in high fidelity, allowing for automatic data collection and analysis across different database silos without prior configuration, enabling sophisticated data trending and knowledge discovery to optimize process plant operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional centralized databases and relational database management systems are used to store process data, then data storage is achieved, but data access efficiency deteriorates due to distributed data storage across multiple databases and systems
Solution Approach 1:
The patent combines multiple distributed databases and data systems into a unified data storage architecture. All process data from various sources (process control systems, laboratory information management systems, enterprise resource planning systems) are stored in a single centralized database, eliminating the need to query multiple separate systems and improving data access efficiency.
Solution Approach 2:
The unified database serves multiple functions simultaneously: it stores process control data, laboratory data, maintenance data, and business data. It also provides multiple access interfaces for different user roles (operators, engineers, managers) and supports various analytical operations, making it a universal data repository for the entire process control environment.
2Ease of manufacture
If data is stored in multiple separate databases and systems, then data organization by function is achieved, but workflow efficiency deteriorates due to cumbersome access procedures
Solution Approach 1:
The patent merges multiple functionally-separated databases into a single unified database that maintains logical organization of data by type and source. This consolidation eliminates the need for operators to navigate between multiple systems while preserving intuitive data structure through standardized schemas and metadata.
Solution Approach 2:
The unified database acts as an intermediary layer between various process control systems and users. It provides standardized access interfaces and data transformation capabilities, allowing users to access data from any source through a common portal without needing to understand the underlying data architecture or origin.
3Loss of energy
If only selected process data is archived in traditional systems, then storage resource constraints are addressed, but troubleshooting accuracy deteriorates due to incomplete historical data
Solution Approach 1:
The system performs preliminary data collection and filtering at the data source before storage. Intelligent agents embedded in process control systems pre-process data, identifying and archiving only relevant information based on predetermined criteria such as alarm conditions, process deviations, and operational significance. This ensures complete archiving of critical data while maintaining efficient storage utilization.
Solution Approach 2:
The patent implements dynamic data archiving strategies where archiving parameters change based on operational conditions. During normal operation, data is archived at standard resolution; during abnormal conditions or troubleshooting scenarios, the system automatically increases data collection frequency and retention period, ensuring complete historical data is available when needed for accurate troubleshooting.
Data Source
AI summary
A big data network or system for a process control system or plant includes a big data apparatus including a data storage area configured to store, using a common data schema, multiple types of process data and/or plant data (such as configuration and real-time data) that is used in, generated by or received by the process control system, and one or more data receiver computing devices to receive the data from multiple nodes or devices. The data may be cached and time-stamped at the nodes and streamed to the big data apparatus for storage. The process control system big data system provides services and/or data analyses to automatically or manually discover prescriptive and/or predictive knowledge, and to determine, based on the discovered knowledge, changes and/or additions to the process control system and to the set of services and/or analyses to optimize the process control system or plant.