Guided Vehicle Machine Difference Data Update
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Solution Overview
Problem
Existing guided vehicle systems do not effectively update machine difference data in real-time, leading to potential inaccuracies in article transfer operations until significant failures occur, and lack autonomous credibility management and error detection for machine data.
Innovation Solution
The system allows guided vehicles to autonomously determine the need for updating machine difference data based on operating conditions, error counts, and time since last update, using sensors to detect errors and travel rail marks, and travel to a transfer position to re-measure and update data, thereby maintaining accuracy and credibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If machine difference data is obtained only when significant failure occurs, then the system operation continuity is maintained, but the accuracy of article transfer operation deteriorates
Solution Approach 1:
The system performs preliminary detection of machine difference changes by monitoring operational parameters (stop position errors, transfer errors, operation counts) before significant failures occur. When predetermined thresholds are exceeded, the system proactively re-obtains machine difference data, preventing accuracy deterioration while maintaining operational continuity.
Solution Approach 2:
The system establishes a feedback mechanism where machine difference data accuracy is continuously monitored through error detection at stop positions and transfer operations. The obtained error information feeds back to the determination means, which decides whether re-measurement is necessary, creating a closed-loop control system that maintains accuracy without interrupting operations.
2Measurement precision
If machine difference data is updated frequently for all guided vehicles, then the accuracy of article transfer operation is maintained, but the system complexity and operational burden increase
Solution Approach 1:
Instead of uniformly updating machine difference data for all guided vehicles, the system applies local quality by individually assessing each guided vehicle's data accuracy needs based on its specific operational conditions. Each vehicle's determination means evaluates its own error rates and operation counts, updating data only when necessary for that specific vehicle, thereby reducing overall system complexity while maintaining local accuracy.
3Measurement precision
If machine difference data is updated based on real-time operational conditions, then the article transfer accuracy is maintained, but the determination and measurement operations become more complex
Solution Approach 1:
Each guided vehicle is equipped with self-service capabilities where the determination means resides within the vehicle itself. The guided vehicle autonomously monitors its own operational parameters, detects when accuracy degradation is likely, and independently decides to re-obtain machine difference data without external intervention, simplifying the overall determination process while maintaining precision.
Data Source
AI summary
Each of guided vehicles has an operating condition memory unit for storing the total travel distance, the travel time, the number of travels, the number of errors at a stop position, and the number of article transfers. These values are evaluated by an evaluation unit 53, and the machine difference is measured again for each of the guided vehicles.