Industrial Risk Assessment via Dynamic Location Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial facilities face challenges in accurately assessing and mitigating risks due to the interplay of static and dynamic data from various equipment and processes, particularly in locations involving human and mobile resources, which can lead to unforeseen hazards and operational inefficiencies.
Innovation Solution
An intelligent risk calculation and mitigation system that integrates static and dynamic inputs, including location data of human and mobile resources, to calculate and manage risks through a risk assessment system and decision support system, enabling informed decision-making and control actions to mitigate potential hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional risk assessment methods are used without location-specific dynamic data, then the system complexity is reduced, but the risk assessment accuracy deteriorates
Solution Approach 1:
The risk assessment system is segmented into multiple independent components: static data management module, dynamic location data collection module (tracking human and mobile resources), risk calculation engine, and decision support module. This segmentation allows each component to handle specific data types and functions independently, improving overall assessment accuracy while managing system complexity through modular architecture.
Solution Approach 2:
The system transitions from traditional static, location-agnostic risk assessment to a multi-dimensional approach by incorporating spatial coordinates and temporal dynamics. Location data of human and mobile resources adds a spatial dimension, while continuous monitoring adds a temporal dimension, enabling precise location-specific risk evaluation that was previously unattainable.
2Reliability
If location data of human and mobile resources is integrated into risk calculation, then the risk mitigation effectiveness is improved, but the data processing complexity increases
Solution Approach 1:
The system introduces intermediate processing layers including data normalization modules, coordinate system transformation engines, and risk zone classification systems. These intermediaries translate raw location data from multiple sources into standardized formats that the risk calculation engine can process efficiently, reducing the complexity burden of handling diverse location data while improving mitigation effectiveness.
Solution Approach 2:
The system performs preliminary actions by pre-defining risk zones, establishing baseline risk profiles for different facility areas, and creating lookup tables for rapid risk evaluation. When location data is received, the system quickly matches current positions against pre-established risk zones rather than performing complete risk calculations from scratch, significantly reducing real-time processing complexity while maintaining high reliability.
3Speed
If dynamic location inputs are continuously monitored, then the responsiveness to hazards is improved, but the energy consumption increases
Solution Approach 1:
The system implements periodic action by monitoring location data at optimized intervals rather than continuously. The monitoring frequency is dynamically adjusted based on risk level: high-risk zones trigger more frequent updates, while low-risk areas use longer intervals. This periodic monitoring approach maintains hazard responsiveness while significantly reducing the energy consumption associated with continuous real-time tracking of all human and mobile resources.
Data Source
AI summary
A system includes a risk assessment system. The risk assessment system includes a risk calculation system configured to calculate a risk based on one or more static inputs and one or more dynamic inputs. The one or more dynamic inputs includes a location of a human resource, a mobile resource, or a combination thereof. The risk assessment system further includes a decision support system (DSS) configured to use the risk to derive one or more decisions based on the risk, the one or more static inputs, and the one or more dynamic inputs. The one or more decisions are configured to aid in operating an industrial facility.