Plant Operation Data Classification for Secure Simulation Control
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Solution Overview
Problem
Conventional technologies for plant operations are limited in managing safe operations as they primarily focus on monitoring pre-set items and simulations, failing to adequately address internal and external factors such as device aging and supply chain variations, leading to potential inefficiencies and safety concerns.
Innovation Solution
An integrated management system, including a CI server, acquires and classifies data from plant devices using attribute information to dynamically manage operations, providing secure and efficient control by determining data provision and simulation suitability based on security levels and operational states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data from plant devices is collected and used for monitoring and simulation, then operational awareness is improved, but data security and confidentiality may be compromised
Solution Approach 1:
The system segments data into multiple categories including identification information, operational information, and state information. Each category is processed and shared differently based on security requirements. This segmentation allows operational awareness to be maintained through appropriate data sharing while protecting sensitive information through differentiated access controls.
Solution Approach 2:
Different security measures and data processing approaches are applied to different types of data based on their sensitivity and security requirements. Identification information receives higher security protection while operational information can be shared more freely. This local quality approach ensures data security is maintained for sensitive information while still providing operational awareness through shared data.
2Reliability
If comprehensive data collection from plant devices is performed, then simulation accuracy and risk management are improved, but system complexity and data processing burden increase
Solution Approach 1:
The system extracts only the necessary data elements required for simulation and risk management purposes from the comprehensive device data. By taking out only the relevant operational information and state information needed for accurate simulation while excluding redundant data, the system maintains simulation accuracy without incurring the full complexity burden of processing all available data.
Solution Approach 2:
The system implements partial data collection by focusing on specific critical parameters and attributes that have the most significant impact on simulation accuracy and risk management. Rather than processing all possible device data, the system selectively collects and processes only the essential portions needed to achieve reliable simulation results, thereby reducing system complexity while maintaining accuracy.
Data Source
AI summary
An information processing apparatus includes: a processor that: acquires, from a device for an operation of a plant, data that is related to the operation of the plant and to which one of pieces of attribute information indicating a state of the device has been assigned; classifies the acquired data into one of the pieces of attribute information based on the attribute information assigned to the acquired data; and operates the plant by using the data classified into one of the pieces of attribute information.