Asset Performance Ranking Using Normalized Monitoring Metrics
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Solution Overview
Problem
Industrial processes face challenges in accurately monitoring and ranking the performance of numerous assets, leading to difficulties in identifying poor-performing assets and prioritizing maintenance efforts due to the complexity of comparing assets of different types and the time-consuming nature of cross-comparison.
Innovation Solution
A computer-implemented method that receives monitored data from assets, generates performance metrics, normalizes them, and creates aggregated metrics to rank assets based on performance, incorporating importance weights and using machine learning models to identify poor-performing assets and recommend mitigation actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional asset monitoring methods are used to track hundreds to thousands of assets, then asset performance can be detected, but it becomes time-consuming and difficult to compare assets of different types and prioritize maintenance efforts
Solution Approach 1:
The patent transforms multiple different performance metrics into a standardized normalized score (0-100 scale) that allows direct comparison across asset types. This parameter transformation enables efficient ranking and identification of poor-performing assets without time-consuming manual cross-comparison
Solution Approach 2:
The patent introduces an intermediary aggregation layer that combines multiple normalized performance metrics into a single aggregated performance metric. This intermediary metric serves as a basis for automated ranking and identification of assets requiring maintenance, significantly reducing the time needed to prioritize maintenance efforts
2Measurement precision
If multiple performance metrics are generated for each asset, then comprehensive performance assessment is achieved, but the complexity of normalizing and comparing metrics across different asset types increases
Solution Approach 1:
The patent applies parameter transformation by converting diverse performance metrics with different units and scales into normalized scores on a common 0-100 scale. This enables accurate cross-asset comparison while simplifying the aggregation process through consistent parameter formats
Solution Approach 2:
The patent creates a universal normalization framework that handles multiple different metric types through a single standardized process. The aggregation function universally combines any number of normalized metrics into a single performance metric, making the system adaptable to various asset types without increasing complexity
Data Source
AI summary
Embodiments of the disclosure provide for monitoring asset performance and ranking of assets based thereon. Such embodiments enable identifying poor-performance assets, determining poor performance factors, and generating action recommendations for mitigating poor performance. Some embodiments receive monitored data associated with assets, generate, for each asset and using the monitored data, performance metrics, normalize the performance metrics for each asset to generate normalized performance metrics for each asset, wherein each performance metric of the normalized performance metrics indicates a level of performance of the corresponding asset. Some embodiments generate an aggregated performance metric for each asset based at least in part on a combination of the plurality of normalized performance metrics corresponding to the asset. Some embodiments generate a ranking of the assets based at least in part on the aggregated performance metric for each asset, wherein the ranking of the assets indicates a level of poor performance for each asset.