Coating Simulation Using Wetness-Aware Spray Pattern Optimization
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Solution Overview
Problem
Existing simulation methods for coating processes, such as painting, do not adequately account for the degree of wetness and uniformity of coating thickness, leading to suboptimal coating results.
Innovation Solution
A simulation method that considers the degree of wetness by superimposing current spray patterns and optimizing coating parameters using geometry data, reference spray patterns, and artificial intelligence to achieve uniform coating thickness and improved coating quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing simulation methods are used to simulate coating processes, then the simulation can be performed with basic geometry data and spray pattern superposition, but the coating uniformity and degree of wetness are not adequately optimized
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing optimal spray patterns in a database for various coating situations. During simulation, these pre-computed reference spray patterns are retrieved and adapted rather than calculating everything from scratch, which improves coating uniformity while managing simulation complexity through preparatory work.
Solution Approach 2:
The patent implements feedback by continuously evaluating the simulated coating result during the simulation loop and adjusting the spray patterns accordingly. The simulation compares the actual coating thickness distribution against target values and iteratively optimizes the spray pattern parameters to achieve desired coating uniformity and degree of wetness.
2Adaptability or versatility
If reference spray patterns are interpolated or mathematically adapted for current painting situations, then simulations can proceed without exact match reference data, but the accuracy of spray pattern representation may be compromised
Solution Approach 1:
The patent applies parameter changes by systematically varying key spray pattern parameters (such as spray angle, fan width, and atomization pressure) around reference values to generate adapted spray patterns that match current painting situations. This allows the simulation to maintain accuracy by making controlled parameter adjustments rather than relying on rough interpolations between discrete reference patterns.
3Manufacturing precision
If the simulation loop optimizes current spray patterns to achieve uniform coating thickness, then coating quality improves, but the computational time and processing requirements increase
Solution Approach 1:
The patent reduces simulation time by performing preliminary calculations and storing optimal spray patterns in advance. The simulation loop only needs to retrieve and adapt these pre-computed patterns rather than performing full optimization calculations for every simulation run, significantly reducing computational time while maintaining coating thickness uniformity.
Solution Approach 2:
The patent applies partial action by focusing the simulation loop optimization only on the most critical spray pattern parameters that have the greatest impact on coating uniformity. Rather than optimizing all possible parameters simultaneously, the method identifies and optimizes only the key parameters, reducing computational effort while achieving satisfactory coating thickness distribution.
Data Source
AI summary
A simulation method for a coating installation including:a) specification of geometric data of the component to be coated,b) specification of general coating parameters,c) specification of starting values of coating parameters to be adjusted, including a coating path and current spray patterns for the individual path points of the coating path, whereby the current spray patterns represent the coating thickness distribution on the component,d) program-controlled execution of a simulation loop, including:calculation of a simulated coating result by computational superimposition of the current spray patterns provided for the individual path points of the coating path, taking into account the degree of wetness,testing the simulated coating result, taking into account the degree of wetness,adjusting the coating parameters to be optimized and repeat the simulation loop if the simulated coating result is not satisfactory,.terminating the simulation loop if the simulated coating result is satisfactory.