Machine Service Interval Scheduling Using Component SOH Feedback
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Solution Overview
Problem
Modern machinery, especially those used in harsh off-highway environments, face challenges in optimally scheduling servicing due to varying service life of components based on usage conditions, leading to unpredictable degradation and potential performance risks or economic losses from frequent or inadequate maintenance.
Innovation Solution
A dynamic service interval scheduling method for electric-drive machines that uses monitoring signals and stored degradation progression profiles to calculate the state-of-health (SOH) of components, generating reporting signals for continued service capacities, enabling informed scheduling decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If service is performed more frequently to prevent component degradation past intended state, then reliability is improved, but productivity deteriorates due to productive time lost
Solution Approach 1:
The patent implements dynamic service interval adjustment based on real-time component health monitoring. Instead of fixed preventive maintenance schedules, the system continuously assesses component conditions and adapts service timing accordingly, allowing extension of service intervals when components are healthy and triggering earlier service when degradation is detected, thus optimizing the balance between reliability and productivity
Solution Approach 2:
The system establishes a feedback loop where component health status is continuously monitored and fed back to the service scheduling system. This feedback mechanism enables data-driven decisions about when service is actually needed versus when components can continue operating, preventing both premature service (which reduces productivity) and delayed service (which reduces reliability)
2Productivity
If service is delayed to maintain productivity, then productivity is improved, but reliability deteriorates due to increased failure risk
Solution Approach 1:
The system performs preliminary health assessments and predicts future component states using degradation models. By anticipating when components will reach critical thresholds, the system can plan service activities in advance during optimal times, preventing unexpected failures while minimizing disruption to productivity. This allows proactive rather than reactive service scheduling
3Ease of operation
If fixed preventive maintenance schedule is used, then ease of operation is improved, but adaptability deteriorates due to inability to account for varying usage conditions
Solution Approach 1:
The system dynamically changes service interval parameters based on actual operating conditions and component responses. Instead of using fixed time or usage-based intervals, the system adjusts maintenance parameters in real-time based on monitored health indicators, environmental conditions, and degradation rates, enabling the schedule to adapt to varying usage patterns while maintaining operational simplicity through automated adjustments
Data Source
AI summary
Dynamic service interval scheduling in a machine includes receiving monitoring signals for a plurality of components in the machine each indicative of an operating characteristic upon which a state-of-health (SOH) of one of the plurality of components is dependent. An SOH term is calculated for each one of the components based on the monitoring signals and a stored SOH degradation progression profile. SOH reporting signals are outputted based on a respective one of the SOH terms. The reporting signals may indicate a plurality of different continued service capacities among the components at least some of which are runtime-independent of one or more components in a drive system in the machine. Related apparatus and control logic is also disclosed.