Laser Cutting Parameterization Using Deterministic Process Models
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Solution Overview
Problem
Current laser machining tools require extensive empirical knowledge and are not reproducible or scalable, as they rely on trial-and-error methods to set parameters for achieving desired machining results, leading to inefficiencies and errors in quality control.
Innovation Solution
A deterministic process model is developed that calculates the physical relationships between laser machining parameters, process characteristics, and machining results, allowing for a simulation-based approach to predict and optimize machining outcomes, including a forecasting method and parameterization method that use conservation equations to model the laser machining process and adapt parameters in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If empirical knowledge and trial-and-error methods are used to set laser machining parameters, then the desired machining result can be achieved, but the method is time-consuming and not reproducible
Solution Approach 1:
The patent creates a database of pre-measured physical relationships between laser parameters and machining results before actual machining operations. This preliminary data collection and modeling eliminates the need for time-consuming trial-and-error parameter setting during production, as the optimal parameters can be directly determined from the pre-established physical models.
Solution Approach 2:
The patent replaces the empirical, experience-based parameter setting method with a physics-based computational model. By substituting the mechanical/trial-and-error approach with a deterministic physical model that calculates optimal parameters based on material properties and desired outcomes, the system achieves both speed and reproducibility.
2Manufacturing precision
If empirical knowledge is used to set machining parameters, then the desired quality can be achieved, but the method is not reproducible and error-prone
Solution Approach 1:
The patent replaces subjective empirical knowledge with objective physics-based calculations. The deterministic model uses fundamental physical relationships to determine optimal parameters, eliminating human error and variability. This ensures that the same input parameters will always produce the same optimal settings, guaranteeing reproducibility across different operators and sessions.
Solution Approach 2:
The patent transforms the parameter setting process from an empirical art to a science by changing the underlying methodology from experience-based guessing to physics-based calculation. By using measurable physical quantities and established physical laws, the system produces consistent, reproducible results that are independent of individual operator expertise.
3Manufacturing precision
If trial-and-error methods are used to determine setting parameters, then the desired machining result can be achieved, but the method is not scalable
Solution Approach 1:
The patent creates a universal physical model that can determine optimal parameters for any material and laser configuration by using fundamental physics relationships. This single model serves multiple functions across different materials, laser types, and machining conditions, eliminating the need for separate trial-and-error processes for each scenario and enabling scalable application across diverse production needs.
4Manufacturing precision
If extensive empirical knowledge is required to operate laser machining tools, then the desired machining result can be achieved, but the operation becomes complex and requires high expertise
Solution Approach 1:
The patent enables the system to determine optimal parameters autonomously by using physics-based models that automatically calculate the correct settings based on input parameters such as material type, thickness, and desired cut quality. This self-determining capability eliminates the need for operators to possess extensive empirical knowledge, as the system performs the complex calculations and parameter optimization automatically.
Data Source
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AI summary
The invention relates to the automatic parameterisation of a laser cutting method based on a target specification for the desired machining result (Etarg) and further relates to the forecasting for a machining result (E) for a specified parameter set for the setting of the laser (L). For this purpose, a deterministic process model (M) is accessed, which is stored in a database (DB) and includes, among other things, process characteristics (PKG).