Objective-Based Vehicle Service Scheduling From Telematics Forecasts
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Solution Overview
Problem
Existing vehicle maintenance schedules fail to account for the varying usage patterns of individual machines, leading to over-maintenance or under-maintenance, resulting in waste or undue risk, as they are based on simple measures of time or usage that do not consider the unique conditions and health of each vehicle.
Innovation Solution
A computer-implemented method and system for objective-based scheduling of vehicle servicing that utilizes vehicle telematics data, including fault codes and component wear metrics, to generate service event forecasts and schedules, prioritizing availability and cost reduction based on an objective function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maintenance is performed according to fixed time or usage intervals, then machine reliability is improved, but maintenance costs increase due to over-maintenance
Solution Approach 1:
The system changes the maintenance parameter from fixed time/usage intervals to dynamic condition-based thresholds. It continuously monitors actual machine conditions (vibration, temperature, wear particles) and adjusts maintenance timing based on real-time parameter changes, enabling maintenance only when actually needed rather than on a fixed schedule.
Solution Approach 2:
The machine performs self-diagnosis through integrated sensors and monitoring systems that automatically detect degradation and trigger maintenance alerts. The system serves itself by identifying when maintenance is needed without external intervention, reducing both over-maintenance and unexpected failures.
2Loss of substance
If maintenance is delayed to reduce costs, then maintenance costs decrease, but machine reliability deteriorates due to under-maintenance
Solution Approach 1:
The system implements continuous feedback loops where sensor data from the machine is constantly monitored and compared against degradation thresholds. When parameters indicate approaching failure conditions, the system automatically generates maintenance alerts, ensuring timely intervention before reliability deteriorates while avoiding unnecessary early maintenance.
Solution Approach 2:
The system performs preliminary detection of degradation trends through continuous monitoring and predicts potential failures before they occur. By identifying early signs of wear or abnormal conditions, it enables proactive maintenance scheduling that prevents reliability deterioration while optimizing maintenance timing.
3Device complexity
If simple time-based scheduling is used, then scheduling complexity is reduced, but adaptability to individual machine conditions deteriorates
Solution Approach 1:
The system creates a universal monitoring platform that can adapt to multiple machine types and conditions through configurable parameters and thresholds. The same core system serves different machines by adjusting monitoring parameters rather than requiring separate scheduling systems for each machine, maintaining simplicity while enabling customization.
4Adaptability or versatility
If individualized maintenance schedules are created for each machine, then adaptability to machine conditions is improved, but scheduling complexity increases
Solution Approach 1:
Each machine effectively creates its own maintenance schedule through self-monitoring and automatic alert generation based on its specific condition parameters. The central system receives standardized alerts from multiple machines and schedules maintenance based on predicted failure times, distributing the complexity management across the fleet rather than requiring centralized complex scheduling for each individual machine.
Data Source
AI summary
Systems and methods for objective-based scheduling of vehicle servicing include: storing an objective function for prioritizing vehicle availability and vehicle maintenance cost reduction; receiving vehicle telemetry data for a vehicle; generating a vehicle service event forecast at least partially based on the vehicle telemetry data; and scheduling a vehicle service event for the vehicle related to the vehicle telemetry data at least partially based on the vehicle service event forecast and the objective function.