Integrated Risk Management Using Geographic and Asset Risk Models
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Solution Overview
Problem
Existing risk management systems are inadequate for integrated management of overall risks in complex systems with multiple assets, as they do not consider the influence of geographical and topographical factors, asset connections, and internal states, leading to unsuitable risk assessment and management.
Innovation Solution
A risk management system that includes a risk modeling unit to generate risk models based on static configuration information, specifying assets and their fault probabilities, and a risk mapping unit to calculate risk evaluation values using dynamic monitoring information, integrating geo-topography, connection, and asset internal risk models to provide comprehensive risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If risk management is performed based on geographical location and natural disasters only, then regional risk assessment is simplified, but integrated management of overall risks considering individual assets and their configurations becomes unsuitable
Solution Approach 1:
The patent segments risk assessment into multiple hierarchical levels: regional risk assessment based on geographical location and natural disasters, asset-specific risk assessment considering individual asset configurations and connections, and integrated overall risk management. This segmentation allows each level to be handled with appropriate complexity while maintaining comprehensive coverage.
Solution Approach 2:
The patent merges multiple risk assessment dimensions including geographical risk factors, asset configuration information, connection relationships between assets, and internal asset states into a unified integrated risk management framework. This combination enables comprehensive risk evaluation that considers both regional contexts and individual asset characteristics.
2Measurement precision
If comprehensive asset configuration information and connection data are collected for accurate risk assessment, then risk evaluation accuracy is improved, but system complexity and information processing requirements increase
Solution Approach 1:
The patent segments information collection and processing into distinct modules: geographical risk data collection, asset configuration information collection, connection relationship data collection, and internal state monitoring. Each module handles specific types of data independently, reducing overall system complexity while enabling comprehensive risk assessment.
Solution Approach 2:
The patent introduces an integrated risk management system as an intermediary that coordinates between various data sources and risk assessment processes. This intermediary manages the complexity of integrating multiple information types while providing accurate risk evaluation outputs.
3Speed
If dynamic monitoring information is continuously processed for real-time risk evaluation, then risk management responsiveness is improved, but computational load and processing time increase
Solution Approach 1:
The patent implements periodic risk evaluation cycles where dynamic monitoring information is processed at predetermined time intervals rather than continuously. This periodic approach maintains real-time risk management responsiveness while significantly reducing computational load and energy consumption compared to continuous processing.
Solution Approach 2:
The patent processes only the necessary portion of dynamic monitoring information required for risk evaluation at each time interval, rather than processing all available data continuously. This partial action approach optimizes computational resource usage while maintaining effective risk management.
Data Source
AI summary
Risk element information indicating risk elements is acquired. An asset capable of becoming a fault due to a risk element indicated in the risk element information, and a fault probability that the asset becomes the fault are specified based on static configuration information. A risk model in which the asset capable of becoming the fault and the fault probability are associated is generated in advance. In response to a designated input, an one asset to be evaluated is specified as an evaluation target asset, based on the designated input. A risk model related to the evaluation target asset is specified. A risk evaluation value being an index indicating a risk of the evaluation target asset is calculated based on the fault probability of the evaluation target asset and the static configuration information. The risk evaluation value of the evaluation target asset is associated with the asset of the risk model.