Digital Twin Simulation for Cargo Static Balancing
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Solution Overview
Problem
Current static balancing methods for cargo transport are inefficient and prone to causing disproportionate wear on transport components due to improper loading, which can result in damage and excessive wear from unbalanced forces.
Innovation Solution
A digital twin simulation system captures property data of cargo items and transport vehicles to generate an optimal loading plan that places the center of gravity in an optimal location, minimizing wear on transport components and ensuring even distribution of weight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional static balancing methods are used to load cargo, then the process is simple and quick, but the center of gravity cannot be precisely calculated and controlled, leading to unbalanced forces and disproportionate wear on transport components
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the physical transport vehicle and cargo items. This digital replica allows for precise simulation and calculation of center of gravity without requiring complex physical measurements or trial-and-error loading methods. The digital model captures all geometric and mass properties, enabling accurate prediction of balancing characteristics before actual loading occurs.
Solution Approach 2:
The patent performs the center of gravity calculation and loading plan optimization in advance using digital twin simulation, before the actual loading process. By pre-calculating the optimal cargo arrangement in the virtual model, the system eliminates the need for complex real-time measurements and adjustments during physical loading, thereby achieving high precision without proportionally increasing operational complexity.
2Reliability
If cargo is loaded without digital twin simulation, then the loading process is faster and simpler, but disproportionate wear on transport components occurs due to unbalanced forces
Solution Approach 1:
The system performs the balancing calculation and loading optimization in advance through digital twin simulation. By determining the optimal cargo arrangement before actual loading, the patent prevents unbalanced forces and component wear from occurring in the first place, rather than requiring time-consuming adjustments or repairs after damage occurs.
Solution Approach 2:
The patent replaces physical trial-and-error loading methods and mechanical balancing adjustments with computational simulation. The digital twin model uses software-based calculations to predict center of gravity and optimize cargo placement, eliminating the need for iterative physical adjustments that would be both time-consuming and potentially damaging to transport components.
3Stability of the object's composition
If digital twin simulation is used to generate loading plans, then static balancing precision is improved and component wear is reduced, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent creates simplified digital representations (twins) of the physical transport vehicle and cargo items that capture only the essential geometric and mass properties needed for balancing calculations. This abstraction allows complex physical systems to be modeled with sufficient accuracy for stability optimization without requiring complete and overly complex digital replicas of all physical components.
Solution Approach 2:
The patent focuses the digital twin simulation on the critical parameters that affect static balancing (mass, center of gravity position, cargo dimensions and placement) while ignoring less relevant details. By changing the level of detail and abstraction in the digital model to match only the necessary parameters for balancing optimization, the system achieves high stability precision without proportionally increasing computational complexity.
Data Source
AI summary
According to one embodiment, a method, computer system, and computer program product for static balancing of a cargo transport through digital twin simulation is provided. The embodiment may include capturing a plurality of property data related to a transport. The embodiment may further include capturing a plurality of property data related to a plurality of cargo items. The embodiment may also include generating a digital twin simulation of the transport and each cargo item. The embodiment may further include generating a loading plan of each cargo item onto the transport based on the generated digital twin simulation.