Agricultural Operation Planning With Support Machine Routing
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Solution Overview
Problem
Agricultural operations face inefficiencies due to overloading at control locations, such as depots, leading to delays and reduced overall efficiency, especially when multiple working regions with varying characteristics are involved.
Innovation Solution
A computer-implemented method determines the optimal number of support machines and operational routes for agricultural operations, considering factors like location, travel time, processing capacity, and working time, to create an efficient operational plan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If more support machines are deployed to working regions, then the working machines can operate faster, but the control location becomes overloaded causing delays
Solution Approach 1:
The system segments the working regions into multiple groups based on their characteristics and requirements. Each group is assigned a specific number of support machines, allowing differentiated resource allocation that prevents overloading at the control location while maintaining high productivity in each segment.
Solution Approach 2:
The system performs preliminary planning by determining the optimal number of support machines for each working region before the operation begins. Routes are pre-calculated and machine allocations are predetermined based on working region characteristics, preventing bottlenecks before they occur.
2Reliability
If support machines wait at the depot to drop off yield, then the depot capacity is respected, but the overall operational efficiency decreases
Solution Approach 1:
The system dynamically adjusts the number of support machines assigned to different working regions based on real-time or planned operational requirements. This dynamic allocation ensures that the depot is not overwhelmed while maintaining high operational efficiency, as machines are distributed optimally across regions rather than queuing at the depot.
Solution Approach 2:
The system acts as an intermediary between the working regions and the control location by strategically positioning support machines in intermediate working regions. This allows yield to be transferred incrementally through multiple regions rather than all machines converging on the control location simultaneously, reducing waiting time and improving efficiency.
3Device complexity
If multiple working regions are served by a single control location, then resource utilization is simplified, but bottlenecks occur at the control location
Solution Approach 1:
The system segments the network of working regions into multiple groups, each with a determined allocation of support machines. This segmentation allows the control location to manage multiple regions efficiently by controlling the flow of machines and yield through planned routes, preventing bottlenecks while maintaining simplified centralized control.
Data Source
AI summary
Methods and systems are provided for planning an agricultural operation associated with an agricultural working environment which includes multiple working regions. A suggested number of support machines is determined for each region. This is used to group multiple regions and an operational route between each region within each group is determined. This is used to generate an operational plan for the overall operation which includes at least a schedule for performance of one or more tasks associated with the working regions.