Hardware Health Scoring for Predictive Maintenance Timing
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Solution Overview
Problem
There is a need for a maintenance system and method to optimize the maintenance of hardware systems by analyzing and creating health information, as existing systems rely on periodic preventive maintenance and do not account for deviations from ideal operational parameters until failures occur.
Innovation Solution
A maintenance system comprising an acquisition circuit to gather operational parameters and an analysis circuit to determine a device health score, remaining useful life, and user recommendations, using machine-learning techniques to process data and provide actionable insights for maintaining hardware systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If periodic preventive maintenance is performed, then unexpected failures are avoided, but maintenance frequency cannot be optimized and equipment may operate outside ideal parameters
Solution Approach 1:
The hardware system performs self-diagnostics by automatically monitoring its own operational parameters and generating health information, eliminating the need for external periodic maintenance checks. The system serves itself by continuously assessing its condition and providing maintenance recommendations.
Solution Approach 2:
The system continuously monitors operational parameters, analyzes health information, and provides feedback through device health scores and maintenance recommendations. This closed-loop feedback enables dynamic optimization of maintenance timing based on actual equipment condition rather than fixed schedules.
2Measurement precision
If continuous monitoring of operational parameters is implemented, then early detection of deviations is achieved, but system complexity increases
Solution Approach 1:
The operational parameters monitoring system serves multiple functions: it tracks equipment health, detects deviations from ideal parameters, generates device health scores, and provides maintenance recommendations. By consolidating these functions into a single integrated system, complexity is managed while achieving comprehensive monitoring.
Solution Approach 2:
The system introduces an intermediary analysis layer that processes raw operational parameters and transforms them into meaningful health information and device health scores. This intermediary layer simplifies the complexity by abstracting detailed parameter monitoring into interpretable health metrics.
3Measurement precision
If machine-learning techniques are used to analyze operational parameters, then accurate health assessment is achieved, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and pre-processing operational parameters during normal operation. This preparation work is done in advance so that when health assessment is needed, the analysis can be performed quickly using pre-processed data, reducing actual processing time.
Solution Approach 2:
The system dynamically adjusts its analysis approach based on operational conditions, focusing computational resources on parameters that show deviations or anomalies. This dynamic prioritization maintains high assessment accuracy while minimizing unnecessary computational processing during normal operation.
Data Source
AI summary
A maintenance system for maintaining a hardware system is described. The maintenance system includes an acquisition circuit and an analysis circuit. The acquisition circuit can be configured to acquire a plurality of operational parameters of the hardware system, the plurality of operational parameters being relevant to a health state of the hardware system. The acquisition circuit can be configured to forward the plurality of operational parameters to the analysis circuit. The analysis circuit can be configured to determine a device health score for the hardware system, a remaining useful life of the hardware system, and/or a user recommendation for operating the hardware system, each based on the plurality of operational parameters. Further, a method of analyzing and/or creating health information for a hardware system is described.