Industrial Plant Observability Framework for Secure Cross-Site Diagnostics
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Solution Overview
Problem
Existing containerized distributed control systems (DCSs) face challenges in achieving efficient, insightful, and secure data observability due to security and privacy concerns, particularly in handling sensitive data across multiple production sites.
Innovation Solution
A multi-site observability system comprising local and global observers, where local observers collect and preprocess data, and a global observer consolidates and analyzes data across sites, incorporating data unification, interpretation, and visualization components to ensure secure and insightful data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensitive observability data is exposed through internet connections for cross-site analysis, then system diagnostic insights are improved, but security and privacy risks increase
Solution Approach 1:
The patent introduces a data intermediary layer that sits between the local DCS systems and the global observability platform. This intermediary performs data anonymization, aggregation, and filtering before transmission, allowing diagnostic insights to be gained while preventing exposure of sensitive proprietary information such as secret ingredients, optimization algorithms, and customer data.
Solution Approach 2:
The patent segments the observability system into local and global components. Local observers collect and pre-process data at each production site, filtering out sensitive information before sending only aggregated, anonymized metrics to the global observer. This segmentation allows cross-site diagnostic analysis while maintaining security boundaries at each location.
2Loss of information
If data from multiple production sites is aggregated and analyzed centrally, then enterprise-level diagnostic capabilities are improved, but data transmission and processing complexity increase
Solution Approach 1:
The patent implements preliminary data processing at local observers before data leaves the production sites. Local observers perform data collection, filtering, aggregation, and anonymization in advance, so that the global observer receives pre-processed, standardized data. This preliminary action reduces the complexity of data transmission and processing at the enterprise level.
Solution Approach 2:
The patent creates a universal data interface and standardized communication protocol that works across all production sites regardless of their specific DCS configurations. The global observer platform is designed to handle diverse data types through a unified processing framework, reducing overall system complexity despite the multi-site aggregation requirement.
3Loss of energy
If local observers pre-process data before transmission, then data security and bandwidth efficiency are improved, but local processing requirements increase
Solution Approach 1:
The patent implements partial pre-processing at local observers, focusing only on essential operations such as filtering sensitive data, aggregating metrics, and basic anonymization. More complex analysis and advanced processing are deferred to the global observer platform with greater computational resources. This partial action approach balances bandwidth efficiency with manageable local processing requirements.
Data Source
AI summary
A method for providing observability data in industrial plant includes obtaining, at a first local observer associated with a first distributed control system, DCS, first data indicative of first observability data associated with the first DCS. The method further comprises pre-processing the first data. The method further comprises providing the pre-processed first data to a global observer for joint processing of the pre-processed first data and pre-processed second data indicative of second observability data associated with a second DCS.