Digital Twin Resource Exchange for Multi-Machine Task Completion
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Solution Overview
Problem
Existing systems fail to seamlessly exchange resources between machines in a multi-machine environment, leading to inefficiencies and incomplete task execution due to insufficient resources, such as low battery levels or inadequate grippers, during digital twin simulations.
Innovation Solution
A system that creates digital twin models of machines, identifies insufficient resources, and exchanges them for required resources based on machine strengths and weaknesses, using detachable parts and battery sharing, validated through digital twin simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing simulation technologies are used in multi-machine environments, then the simulation can be executed, but resource allocation is ineffective and machines with insufficient resources cannot complete tasks safely
Solution Approach 1:
The patent creates digital twin models that are virtual copies of physical machines, allowing simulation and resource allocation to be tested in the virtual environment before execution. The digital twin includes complete machine specifications, current resource states, and capability definitions, enabling effective resource allocation without risking actual task safety.
Solution Approach 2:
The system continuously monitors machine resource states (battery levels, gripper capacity, etc.) and feeds this information back to the resource allocation module. This feedback mechanism allows the system to dynamically adjust resource allocation based on current machine states, ensuring both safety and efficiency.
2Productivity
If machines operate without adequate resource allocation simulation, then operations can proceed quickly, but tasks may be incomplete or unsafe
Solution Approach 1:
The system performs resource allocation simulation and validation in advance before actual task execution. By pre-assessing whether machines have sufficient resources (battery, gripper strength, etc.) and pre-arranging resource exchanges, the system ensures task safety is guaranteed before operations begin, eliminating the need for slow real-time adjustments during execution.
3Productivity
If digital twin simulation with resource exchange is implemented, then resource allocation efficiency improves, but system complexity increases
Solution Approach 1:
The patent segments the machine into distinct components with specific resources (battery, gripper, motor, etc.), allowing independent monitoring and allocation of each resource type. This segmentation simplifies the complexity by breaking down the overall resource management problem into manageable, discrete resource units that can be independently tracked and exchanged.
Data Source
AI summary
An embodiment for simulating an exchange of resources in a multi-machine environment is provided. The embodiment may include receiving data relating to an activity and one or more machines to perform the activity. The embodiment may also include identifying each part of the one or more machines. The embodiment may further include creating a digital twin model of each identified part. The embodiment may also include executing a digital twin simulation of the activity. The embodiment may further include in response to determining at least one machine is associated with an insufficient resource, identifying a required resource and at least one machine having the required resource. The embodiment may also include exchanging the insufficient resource of the at least one machine associated with the insufficient resource for the required resource of the at least one machine having the required resource.