Dynamic Risk Calculation Engine for Turbomachine Reliability
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Solution Overview
Problem
Complex machine systems, such as turbomachines, face challenges in efficiently predicting and managing reliability and risk due to their intricate nature, leading to time-consuming and costly processes for safety instrumented systems (SIS) modeling, especially when each installation requires unique modeling without reuse of previous data.
Innovation Solution
A dynamic risk calculation engine (DRCE) system is introduced, which includes a model library of reusable subsystem models, allowing for real-time risk calculation and maintenance policy inputs to derive system risk, and a run-time risk calculation engine to drive actions based on reliability measures, using techniques like Markov models, Fault Tree Analysis, and layer of protection analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If unique modeling is performed for each installation, then reliability prediction accuracy is improved, but time consumption and complexity increase
Solution Approach 1:
The system segments the reliability modeling process into reusable subsystem models (e.g., turbine, compressor, heat exchanger modules) that can be independently developed, validated, and then assembled into installation-specific configurations. This allows accurate reliability prediction through customized modeling while reducing overall modeling time through component reuse.
Solution Approach 2:
The patent implements a library of pre-developed subsystem models that can be copied and reused across multiple installations. These standardized models capture proven reliability characteristics and can be rapidly deployed to new projects, significantly reducing modeling time while maintaining accuracy through consistent, validated model structures.
2Reliability
If comprehensive safety instrumented system modeling is performed, then safety reliability is improved, but device complexity increases
Solution Approach 1:
The SIS is divided into functional subsystems (sensors, logic solvers, final elements) with dedicated reusable models for each. This segmentation allows comprehensive safety modeling through detailed subsystem analysis while reducing overall complexity by breaking down the complex SIS into manageable, standardized components.
Solution Approach 2:
The patent creates universal subsystem models that can represent multiple SIS components and configurations through parameterization. A single sensor model template, for example, can represent various sensor types by adjusting parameters, reducing modeling complexity while maintaining comprehensive safety coverage.
3Measurement precision
If detailed failure analysis is conducted for each component, then risk prediction accuracy is improved, but productivity decreases
Solution Approach 1:
The patent performs detailed failure analysis and model development in advance, creating a library of pre-analyzed subsystem models with embedded failure mechanisms and risk characteristics. This preliminary action enables rapid deployment to multiple installations without repeating the detailed analysis work, improving productivity while maintaining high risk prediction accuracy through the use of pre-validates models.
Data Source
AI summary
A system may include a dynamic risk calculation engine (DRCE) system. The DRCE includes a model library configured to model a system, wherein the model library comprises a plurality of subsystem models, and each of the plurality of subsystem models is configured to derive a reliability measure. The DRCE further includes a fault tolerance input and a maintenance policy input. The DRCE additionally includes a run-time risk calculation engine configured to use a user-defined set of the plurality of subsystem models, the fault tolerance input, and the maintenance policy input, to derive a system risk for an apparatus.