M2M Payload Control for Off-Highway Haulage Machines
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Solution Overview
Problem
Existing machine-to-machine communication systems for payload control in off-highway trucks do not effectively account for varying distribution characteristics of different materials, leading to potential overloading and uneven distribution, which can result in increased tire wear, reduced productivity, and machine stress.
Innovation Solution
A method and system utilizing machine-to-machine communication to determine the payload and distribution within haulage machines, allowing loading machines to receive signals on the amount and position of additional payload needed to achieve optimal distribution, ensuring even loading and preventing overloading through real-time data exchange and visual feedback to operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the hauling machine is filled to capacity based on simple volume monitoring, then the quantity of material transported is maximized, but the payload distribution becomes uneven and the machine may be overloaded
Solution Approach 1:
The system implements continuous feedback by monitoring payload distribution in real-time during loading and communicating this information back to the loading machine. The hauling machine determines current payload distribution and transmits this data to the loading machine, which then adjusts subsequent material deposition based on the feedback received, enabling dynamic optimization of payload distribution.
Solution Approach 2:
The system performs preliminary determination of payload distribution before the final work cycle is completed. By monitoring and calculating payload distribution during the loading process and determining the status before the last work cycle, the system can proactively adjust the loading strategy to achieve optimal distribution in the final configuration.
2Productivity
If material is loaded without considering distribution characteristics of different materials, then the loading process is simplified and faster, but the payload distribution becomes uneven and machine stress increases
Solution Approach 1:
The system dynamically adapts the loading strategy based on the specific material being loaded. Different material types with different distribution characteristics are handled with customized deposition patterns and locations. The system modifies loading parameters in real-time according to the material properties and current payload distribution state, rather than using a static loading approach.
Solution Approach 2:
The system applies different loading strategies to different regions of the hauling machine based on local requirements. Material is deposited at specific locations within the payload carrier depending on the current distribution needs, material type, and target configuration. This localized approach to material deposition ensures optimal distribution while maintaining efficient loading.
3Ease of operation
If the loading machine deposits material without precise location control, then the operation is simpler and more efficient, but the payload distribution is uneven and ride control deteriorates
Solution Approach 1:
The system replaces manual operator judgment and mechanical positioning with automated electronic monitoring and control. Sensors, GPS, and communication systems automatically determine optimal deposition locations and guide the loading machine, eliminating the need for complex manual calculations and observations while achieving precise payload distribution.
Solution Approach 2:
The system introduces an intermediary communication system between the hauling machine and loading machine. This intermediary transmits payload distribution data and deposition guidance information, enabling coordinated control without requiring direct mechanical coupling or complex manual coordination between the two machines.
Data Source
AI summary
A method for enhancing payload control is disclosed. The method includes removing material during a plurality of work cycles with at least one loading machine and associating the loading machine relative to at least one haulage machine. The method also includes determining the relative locations of the loading machine and the haulage machine and, during the plurality of work cycles, loading removed material into the haulage machine with the loading machine. The method also includes determining payload and payload distribution within the haulage machine at least before a last work cycle of the plurality of work cycles and communicating to the loading machine, via a machine-to-machine communication system, the amount and position within the haulage machine of additional payload desired in at least the last work cycle of the plurality of work cycles for desired payload and payload distribution.