Shared Moving-Object Fleet Maintenance via Part-Level Monitoring
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Solution Overview
Problem
The challenge of managing and maintaining a large number of shared moving objects in densely populated areas is complex, leading to potential safety issues and reduced operational efficiency due to inadequate maintenance, which can result in human accidents and inefficient resource allocation.
Innovation Solution
A method and system for maintaining moving objects in a fleet system using a computing device that monitors parts, analyzes maintenance levels, and determines timely maintenance based on essential or potential levels, considering additional data and resource requirements, and requests maintenance when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maintenance is performed whenever a problem occurs in a part, then the reliability of the moving object is improved, but the productivity of the fleet system deteriorates due to excessive maintenance resources and reduced operation rate
Solution Approach 1:
The system performs preliminary maintenance actions by predicting part failures before they occur using machine learning models that analyze monitoring data. This allows the fleet system to schedule maintenance proactively rather than reactively, improving reliability while minimizing disruption to operations.
Solution Approach 2:
The system implements continuous feedback loops where monitoring information from moving objects is fed into machine learning models to predict maintenance needs. This feedback mechanism enables dynamic adjustment of maintenance schedules based on actual part condition, optimizing both reliability and productivity.
2Ease of operation
If a large number of shared moving objects are stored and managed in the vicinity of densely populated areas, then the ease of operation is improved for users, but the device complexity of the fleet system increases making it impossible to finely manage various parts
Solution Approach 1:
The moving objects themselves perform self-monitoring and self-diagnosis through onboard sensors and communication modules. They automatically transmit monitoring information to the fleet system and can initiate maintenance requests independently, reducing the complexity burden on the central management system while maintaining ease of operation for users.
Solution Approach 2:
The maintenance management function is segmented and distributed across multiple moving objects rather than centralized. Each object has its own monitoring and communication capabilities, allowing the system to manage large fleets efficiently by distributing the management burden across individual units.
3Reliability
If the operation rate of shared moving objects is lowered due to maintenance, then the reliability is improved, but the productivity of the fleet system deteriorates and the fleet system cannot assign moving objects in response to use requests
Solution Approach 1:
The system performs preliminary maintenance actions by predicting part failures before they occur using machine learning models that analyze monitoring data. This allows the fleet system to schedule maintenance proactively rather than reactively, improving reliability while minimizing disruption to operations.
Solution Approach 2:
The maintenance scheduling system dynamically adjusts maintenance timing based on real-time monitoring data and predicted part conditions. This dynamic approach allows the system to optimize maintenance windows to minimize impact on fleet productivity while ensuring reliability.
Data Source
AI summary
A method of maintaining a moving object for a fleet system includes obtaining monitoring information of parts, analyzing a maintenance level of each of the parts from the monitoring information, checking whether there is a part corresponding to an essential level or a potential level as the maintenance level, and determining whether to maintain the part of the moving object and requesting maintenance of the part according to the determination, when the part reaches the essential level or when the part reaches the potential level and a predetermined condition is satisfied. If at least one of mileage data or use period data of the monitoring information is lower than a standard maintenance value of the part, the maintenance level of the part is able to reach the essential level.