Process Plant Smart Search with Data Diode Remote Access
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Solution Overview
Problem
Process control systems in industrial plants face challenges in providing secure and efficient search functionality for process plant-related data, especially when accessed remotely, due to the complexity and distribution of data across various subsystems, and the risk of cyber intrusions which can lead to operational disruptions and safety hazards.
Innovation Solution
A system that includes a process plant search query server capable of analyzing search queries using contextual knowledge repositories and temporal databases, providing ranked search results, and securely delivering data to external systems through an edge gateway system with unidirectional data diodes to prevent cyber threats, allowing remote access while maintaining data integrity and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If process plant data is made accessible remotely through centralized hardware devices, then operator accessibility and efficiency are improved, but the system becomes vulnerable to cyber intrusions and security threats
Solution Approach 1:
The system segments data access by implementing localized edge computing devices at different plant locations, each capable of independent data processing and search operations. This segmentation allows remote access functionality to be distributed across multiple isolated nodes rather than centralized, reducing the attack surface for cyber intrusions while maintaining operator accessibility.
Solution Approach 2:
The patent introduces unidirectional data diodes as intermediary components between the process control system and external networks. These diodes allow data to flow only in one direction (from the control system to external devices), preventing reverse infiltration while enabling remote access. This intermediary mechanism resolves the security contradiction by permitting accessibility without exposing the core system to bidirectional threats.
2Measurement precision
If search functionality is enhanced with contextual knowledge repositories and temporal databases, then search accuracy and relevance are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system pre-processes and structures process plant data into contextual knowledge repositories and temporal databases before search operations are initiated. By organizing data with metadata, relationships, and temporal context in advance, the system enables accurate search results without adding complexity to the search execution process itself. The heavy lifting of data organization occurs beforehand, simplifying the actual search operation.
Solution Approach 2:
The patent adds contextual and temporal dimensions to the search capability by integrating knowledge graphs and time-series data structures. Rather than simply searching through flat data sets, the system operates in enhanced dimensional spaces that include entity relationships, contextual metadata, and temporal sequences. This dimensional enhancement improves search accuracy without proportionally increasing system complexity, as the additional dimensions are layered onto existing data infrastructure.
3Reliability
If data is distributed across multiple subsystems and devices, then system reliability and fault tolerance are improved, but data retrieval and search operations become more difficult
Solution Approach 1:
The patent implements universal search interfaces and standardized data access protocols that work consistently across all distributed subsystems and devices. Rather than requiring different access methods for different data locations, the system provides a unified search mechanism that transparently queries across the entire distributed architecture. This universality maintains reliability through distribution while eliminating the retrieval complexity that would otherwise result from data scattering.
Solution Approach 2:
The system employs feedback mechanisms where search results include contextual information about data sources, retrieval paths, and relevance metrics. This feedback loop allows the search interface to adapt and refine results based on the distributed nature of the data, providing users with clear information about where data originates and how it was retrieved. The feedback mechanism transforms the complexity of distributed data retrieval into actionable, interpretable results for operators.
Data Source
AI summary
To provide enhanced search capabilities in a process control system, a knowledge repository is generated that includes both contextual data and time series data. The contextual data organizes process plant-related data according to semantic relations between the process plant-related data and the process plant entities. When a user submits a process plant search query related to process plant entities within a process plant, search results are obtained by identifying a data set from the knowledge repository. The contextual data categorizes process parameters so that users can search for a particular process parameter category. Users can tag previous searches to execute them once again at a later time. Users can also execute queries for predicted or future states of process plant entities, batch queries regarding batch processes, soft sensor analytics and monitoring applications, parameter lifecycle applications, perturbation applications, step testing applications, or batch provisioning and scheduling applications using the knowledge repository.