Unmanned Lawn Mower Maintenance Timing Using Server Case Feedback
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Solution Overview
Problem
Existing unmanned lawn mowers lack an efficient method to determine the optimal maintenance time, leading to excessive maintenance due to varying cumulative work times across different machines.
Innovation Solution
An unmanned work system where machines communicate with a management server to transmit operation information, which stores failure and maintenance cases, allowing for determination and notification of necessary maintenance based on specific criteria and image data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If cumulative work time is used as a fixed criterion for maintenance notification, then maintenance timing can be determined simply, but maintenance becomes excessive for individual machines with varying work conditions
Solution Approach 1:
The system changes from using a single fixed parameter (cumulative work time) to multiple dynamic parameters including operation load, environmental conditions, and actual machine state data. This allows maintenance timing to be adjusted based on actual usage patterns rather than a universal schedule, resolving the contradiction between simplicity and accuracy.
Solution Approach 2:
The system implements feedback mechanisms where maintenance notifications are sent back to both the user and the machine based on analyzed operation data. This closed-loop approach allows the system to learn from actual machine performance and adjust maintenance timing accordingly, improving accuracy while maintaining automated operation.
2Ease of manufacture
If maintenance is performed based on fixed cumulative work time thresholds, then maintenance scheduling is straightforward, but unnecessary maintenance occurs reducing productivity
Solution Approach 1:
The maintenance scheduling system transitions from a static fixed-time approach to a dynamic adaptive approach. The system continuously monitors operation load, environmental factors, and machine response characteristics to dynamically adjust maintenance timing. This ensures maintenance is performed only when actually needed, maximizing machine productivity while maintaining reliability.
Solution Approach 2:
The system performs preliminary analysis of operation data and machine state before issuing maintenance notifications. By predicting when maintenance will be needed based on current trends and historical data, the system can schedule maintenance in advance without causing unnecessary downtime, thus preserving productivity while ensuring timely service.
Data Source
AI summary
An unmanned lawn mowing system includes a plurality of unmanned lawn mowers that perform work while traveling without a human operator and a management server. Each of the unmanned lawn mowers includes an information transmission section that transmits operation information including information indicating a work state to the management server. The management server includes: a case storage section that stores a case related to a failure in and/or a case related to maintenance of each of the unmanned lawn mowers; a maintenance determination section that determines whether or not maintenance of the unmanned lawn mower is necessary, based on the case associated with operation information identical or similar to the operation information; and a maintenance notification transmission section that notifies maintenance to the unmanned lawn mowers, based on a determination result made by the maintenance determination section.