Agricultural Machine Coordination via Dynamic Workflow Simulation
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Solution Overview
Problem
Current methods for coordinating multiple mobile agricultural machines to share resources or work together are inefficient, leading to high downtimes and economic losses due to uncertainties in meeting points and unbalanced load distribution, especially over long distances.
Innovation Solution
A method that dynamically resimulates workflows and redefines meeting points and paths for machines to optimize resource allocation, utilizing a central processing unit and decentralized units for real-time communication and navigation, allowing for flexible route adjustments and machine substitution to minimize downtime and operational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the number of transport vehicles is reduced, then their downtimes are reduced, but the occasional standstill of a harvesting machine has to be accepted because no transport vehicle is available in time for unloading
Solution Approach 1:
The patent implements dynamic workflow simulation and resimulation that continuously adapts to changing conditions. The system dynamically recalculates meeting points and adjusts workflows in real-time based on actual machine positions, speeds, and tank levels, allowing the coordination system to flexibly respond to variations in harvesting pace and transport availability without requiring fixed, rigid schedules
Solution Approach 2:
The system employs continuous feedback mechanisms by monitoring actual machine positions, tank fill levels, and workflow progress against simulated plans. When deviations occur (such as harvesting progressing faster or slower than expected), the system detects these changes and triggers resimulation to recalculate optimal meeting points and adjust transport vehicle dispatch timing, ensuring adaptive coordination
2Area of stationary object
If the distance to be covered by the transport vehicle is increased, then more areas can be served, but the request from the harvesting machine must come earlier and the forecast becomes more uncertain
Solution Approach 1:
The system performs preliminary workflow simulation before actual harvesting operations to pre-calculate optimal meeting points and transport dispatch timing. By simulating the entire workflow in advance considering machine speeds, tank capacities, and distances, the system establishes preliminary plans that are then executed and adjusted in real-time, allowing transport vehicles to be dispatched optimally even for distant locations
Solution Approach 2:
The meeting point calculation is made dynamic rather than fixed. The system continuously updates the optimal meeting point based on actual machine positions, velocities, and remaining crop quantities. This dynamic recalculation allows the system to adapt to changing conditions during harvesting, maintaining forecast accuracy even over long distances where conditions may change significantly
3Productivity
If a central control system is implemented to coordinate multiple machines, then resource allocation is optimized, but the system complexity increases
Solution Approach 1:
The system enables machines to self-report their status (position, tank level, workflow progress) automatically through onboard sensors and communication devices. Each machine essentially serves itself by providing data to the central system, which then uses this self-reported information to calculate optimal meeting points and coordinate transport dispatch, reducing the need for manual monitoring and control intervention
Solution Approach 2:
The system focuses on calculating and optimizing key parameters (meeting point location, dispatch timing, route selection) rather than controlling every aspect of machine operation. By changing and optimizing these critical coordination parameters dynamically based on simulated workflows and actual conditions, the system achieves effective resource allocation without requiring complex control of all operational details
Data Source
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AI summary
The method involves simulating operating cycles for mobile agricultural machines (1, 2) such that a conflict with usage of transport vehicles (3, 4) is avoided by correctly performing the simulated operating cycles. The simulated operating cycles are signalized to the machines. Operating cycles are newly simulated based on actual operating conditions of the machines. The newly simulated cycles are signalized when a deviation is occurred between a real operating condition of the machine and operating condition performed according to the newly simulated cycles. Independent claims are also included for the following: (1) a control device with a processing unit and an interface for use in communication with a mobile agricultural machine (2) a computer program product with a set of instructions for a method for coordinating multiple mobile agricultural machines.