Hybrid Adaptively Sampled Distance Fields for Machining Simulation
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Solution Overview
Problem
Current methods for simulating numerically controlled (NC) machining face challenges in achieving high precision due to limitations in representing and rendering swept volumes, leading to discrepancies in the final shape of workpieces, which can result in undesirable gouges or nicks, and require time-consuming and expensive manual testing.
Innovation Solution
The implementation of a hybrid adaptively sampled distance field (ADF) that uses a spatial hierarchy of cells with both distance samples and functions, allowing for efficient representation and reconstruction of high precision models, enabling accurate simulation and rendering of machining processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing with physical workpieces is used to detect surface defects, then measurement precision can be achieved, but loss of time and productivity are significantly worsened
Solution Approach 1:
The patent creates a virtual copy of the physical machining process through computer simulation. The simulation model replicates the workpiece, cutting tool, and machining operations in a virtual environment, allowing defect detection without physical testing. This copying approach maintains measurement precision while eliminating time-consuming manual testing iterations.
2Loss of time
If computer-based simulation is used to detect surface defects, then loss of time is reduced, but measurement precision deteriorates due to modeling approximations
Solution Approach 1:
The patent dynamically adjusts simulation parameters including mesh resolution, material property accuracy, and contact mechanics models to achieve the required measurement precision. By changing these parameters based on the specific detection requirements, the simulation maintains high precision for surface defect detection while keeping computational time reasonable.
Solution Approach 2:
The patent replaces physical mechanical testing with computational mechanics-based simulation. Instead of physically machining test workpieces and inspecting them, the system uses finite element analysis and computational models to predict surface defects, substituting mechanical testing with digital simulation that maintains precision while reducing time.
3Manufacturing precision
If high precision modeling of swept volumes is implemented, then manufacturing precision is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent segments the complex swept volume modeling into discrete computational elements including mesh grids, finite elements, and localized refinement zones. By dividing the workpiece and tool paths into manageable segments, the system achieves high manufacturing precision for complex geometries while keeping the computational model complexity manageable through systematic decomposition.
Solution Approach 2:
The patent applies local quality enhancement by using adaptive mesh refinement that concentrates computational resources in regions where high precision is critical, such as areas prone to surface defects or complex tool-path interactions. This localized approach maintains manufacturing precision where needed while reducing overall model complexity in less critical regions.
Data Source
AI summary
A computer program product for processing a model of an object according to a set of instructions includes a non-transitory computer-readable memory storing a model of an object represented by a hybrid adaptively sampled distance field (ADF), wherein the model includes a hierarchy of cells, wherein at least one cell includes a set of distance functions forming at least part of a boundary of the object and a set of distance samples of at least some of the distance functions, such that a processor executing the set of instructions processes the model of the object.