Combination Weighing Digital Twin for Sticky Product Flow
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Solution Overview
Problem
Existing combination scales, particularly in the food and food processing industries, face challenges such as product jams and malfunctions due to handling sticky or elongated products, requiring extensive and costly testing to determine suitable control parameters and configurations.
Innovation Solution
A method involving a digital model and numerical simulation to adapt and optimize control data sets for scales based on product properties, simulating product movement and behavior to minimize jams and optimize throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive real-world testing is conducted to determine suitable control parameters for sticky or elongated products, then the reliability of scale operation is improved, but the time and cost required for configuration increases significantly
Solution Approach 1:
The patent applies preliminary action by performing virtual testing and simulation before actual scale deployment. A digital twin model replicates the scale's behavior and product interactions, allowing control parameters to be optimized in advance through computational experiments rather than physical testing. This preliminary virtual configuration reduces both time and cost while ensuring reliable operation when the scale is deployed with sticky or elongated products.
Solution Approach 2:
The patent creates a digital copy (digital twin) of the physical scale system that replicates its geometry, material properties, and operational behavior. This virtual copy allows extensive testing and parameter optimization without affecting the actual scale or requiring physical product testing. The digital twin accurately mimics product-surface interactions, enabling reliable parameter determination through simulation rather than costly real-world experimentation.
2Manufacturing precision
If extensive real-world testing is conducted to determine suitable control parameters, then the manufacturing precision of scale configuration is improved, but the cost and complexity of the process increases
Solution Approach 1:
The patent replaces the mechanical testing system with a computational simulation system. Instead of physically testing the scale with actual products to determine control parameters, the system uses a digital twin model with numerical solvers to simulate product-surface interactions. This substitution maintains high configuration precision while eliminating the complexity and cost of physical testing infrastructure, equipment, and material consumption.
Solution Approach 2:
The digital twin creates a virtual replica of the scale system that preserves all geometric and physical properties needed for accurate configuration. This copy enables precise parameter determination through simulation, replacing complex physical testing procedures with computationally efficient virtual experiments that maintain manufacturing precision without requiring complex testing apparatus or extensive physical setup.
3Productivity
If a digital twin model and numerical simulation are used to optimize control parameters, then the productivity of scale configuration is improved, but the computational resources and model complexity increase
Solution Approach 1:
The patent segments the configuration process into distinct computational stages: building the digital twin model, setting up numerical solvers, running simulations with different control parameters, and optimizing based on simulation results. This segmentation allows each stage to be independently optimized and executed, improving overall configuration productivity. The complex simulation model is broken down into manageable computational tasks that can be systematically processed rather than requiring monolithic complex testing procedures.
Data Source
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AI summary
The present invention relates to a simulation of the operation of a scale, in particular a combination scale, using a digital model of the scale and its sub-components, as well as a numerical simulation, in particular a product simulation. For this purpose, a digital model of the scale is created, and a product simulation of the scale's operation is performed. Then, the scale's control parameters are optimized.