Machine Health Index Modeling for Real-Time Risk Assessment
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Solution Overview
Problem
Machine operators and insurers lack real-time information on the current state and future deterioration of machines, making it difficult to assess insurance risks, expected lifetimes, and residual values, leading to unclear contract terms and potential misalignment with actual machine conditions.
Innovation Solution
A method for calculating a health characteristic variable using a machine data detection unit to gather performance and infrastructure data, which is then processed through an individual function to provide a real-time health index, incorporating historical observations and maintenance schedules to adjust insurance rates dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time machine health monitoring is implemented, then insurance risk assessment accuracy is improved, but system complexity and data processing requirements increase
Solution Approach 1:
A health characteristic variable is introduced as an intermediary metric that translates complex machine state data into a single interpretable indicator. This mediator variable synthesizes multiple sensor inputs and operational parameters into one comprehensive health assessment, reducing the complexity of direct monitoring while maintaining measurement precision.
Solution Approach 2:
Instead of directly monitoring all raw machine parameters in real-time, the system creates a simplified copy or representation of machine health through the health characteristic variable. This virtual model replicates the essential health state without requiring direct measurement of every physical parameter, reducing system complexity.
2Adaptability or versatility
If dynamic insurance rates are implemented based on real-time machine data, then insurance contract relevance is improved, but data processing and calculation complexity increase
Solution Approach 1:
The system dynamically changes the insurance rate parameter based on variations in the health characteristic variable. Instead of complex multi-parameter calculations, the insurance terms are adjusted according to changes in the single health indicator, enabling contract adaptability while simplifying the calculation mechanism.
3Measurement precision
If fine-grained machine data is collected for health assessment, then measurement precision is improved, but information processing requirements and system complexity increase
Solution Approach 1:
The system extracts only the essential information needed for health assessment from the full set of machine data. The health characteristic variable is derived by selecting and processing only the critical parameters and features from the available data stream, eliminating unnecessary information while maintaining measurement precision.
Data Source
AI summary
Method and apparatus for ascertaining a at a current time of consideration and for future times of consideration, wherein a first time profile of a base characteristic variable is mapped over the operating time, where the first time profile of the base characteristic variable represents a state of a reference machine at the time of consideration in dependence on the operating time and an actual characteristic variable that varies over the operating time be calculated by means of an individual function, where an input variable fed to the individual function is a performance characteristic variable of the machine, which is detected periodically via a machine data detection unit or is predicted for future operating times, and where the health characteristic variable is displayed as a second time profile by adding the ascertained actual characteristic variable or the predicted actual characteristic variable to the first time profile.