Generative 3D Shape Layering for 2.5-Axis Milling
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Solution Overview
Problem
Current CAD software limitations in generating designs for 2.5-axis subtractive manufacturing processes, which require efficient manufacturing methods that can handle complex geometries and multiple milling directions without repositioning the workpiece, are not adequately addressed by existing generative design solvers that operate directly on exact surface boundary representations.
Innovation Solution
A computer-aided design method that iteratively modifies a density-based representation of a 3D shape in accordance with milling directions, adjusting density values and grouping elements into discrete layers to facilitate 2.5-axis machining, using numerical simulations and sensitivity analysis to optimize the design for efficient manufacturing processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If generative design solvers operate directly on exact surface boundary representations (B-Rep), then manufacturing precision is improved, but device complexity increases and manufacturing time increases for 2.5-axis processes
Solution Approach 1:
The patent segments the manufacturing process into distinct phases: roughing operations that remove bulk material and finishing operations that achieve final precision. This segmentation allows the use of simplified volumetric representations during roughing while reserving exact B-Rep for precision-critical finishing operations, thereby reducing overall solver complexity without sacrificing manufacturing precision.
Solution Approach 2:
The patent introduces a new dimension of manufacturing process planning by integrating 2.5-axis specific constraints into the generative design solver. This includes determining optimal layer boundaries and milling directions, which adds a process-oriented dimension to the traditional geometry-only design approach, enabling simplified representations to work effectively within constrained manufacturing paradigms.
2Productivity
If multiple milling directions are used without repositioning the workpiece, then productivity is improved, but manufacturing precision deteriorates due to tool accessibility constraints
Solution Approach 1:
The patent employs dynamic toolpath generation that adapts milling directions based on local geometry features and accessibility constraints. The solver dynamically determines optimal milling directions for each region of the part, allowing multiple directions to be used within a single setup while maintaining precision through real-time adaptation of cutting parameters and tool orientations.
Solution Approach 2:
The patent uses voxel-based copies or simplified representations of the part geometry to pre-determine feasible milling directions and identify tool accessibility issues before actual machining. This allows the system to plan multiple milling directions that avoid precision-critical regions, then execute those pre-validated paths on the actual part with confidence in maintaining surface finish quality.
3Adaptability or versatility
If complex geometries are generated for 2.5-axis machining, then adaptability is improved, but loss of time increases due to extended manufacturing cycles
Solution Approach 1:
The patent changes key parameters of the generative design process by incorporating 2.5-axis specific constraints such as maximum tool diameter, minimum milling depth, and layer boundary requirements. These parameter changes guide the topology optimization to produce geometries that are inherently more suitable for 2.5-axis machining, reducing the need for time-consuming post-processing and toolpath adjustments while maintaining design flexibility within the constrained parameter space.
4Ease of manufacture
If layer boundary determination is integrated into generative design, then ease of manufacture is improved, but device complexity increases due to additional computational requirements
Solution Approach 1:
The patent merges the layer boundary determination function directly into the topology optimization solver, eliminating the need for separate post-processing steps. By combining these functions into a single integrated computational framework, the system improves ease of manufacture through automated layer planning while managing software complexity through unified algorithmic architecture rather than multiple separate tools.
Data Source
AI summary
Methods, systems, and apparatus, including medium-encoded computer program products, include: obtaining one or more design criteria for a modeled object; iteratively modifying a three-dimensional shape of the modeled object in accordance with the one or more design criteria, determining layer boundaries between three or more discrete layers for the three-dimensional shape based on differences among multiple milling depths identified for respective milling lines in a density-based representation of the three-dimensional shape, including adjusting the density-based representation of the three-dimensional shape to reassign milling depths for at least a portion of the milling lines such that the milling depths for the milling lines correspond to the layer boundaries between the three or more discrete layers for the three-dimensional shape, thereby changing the three-dimensional shape of the modeled object; and providing the three-dimensional shape of the modeled object for use in manufacturing a physical structure using a 2.5-axis subtractive manufacturing process.