3D Printing Part Nesting With Parallel Batch Positioning
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Solution Overview
Problem
Current 3D printing technologies face challenges in optimizing the nesting of parts within a printing space, leading to inefficient use of space and materials, as existing methods lack effective parallelization and adaptive positioning strategies.
Innovation Solution
A method that splits part models into batches, defines roadmaps and positioning rules for each batch, and optimizes part positioning schemes in parallel, using probabilistic roadmap and rapidly-exploring random tree algorithms to efficiently nest parts within the available space, incorporating constraints and requirements for supports and interlocking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sequential nesting methods are used, then positioning accuracy can be maintained, but nesting time and computational resources increase significantly
Solution Approach 1:
The patent divides the nesting problem into hierarchical levels: (1) splitting part models into batches, (2) defining roadmaps for each batch, and (3) optimizing positioning within each batch independently. This segmentation allows parallel processing of multiple batches while maintaining overall positioning accuracy, resolving the contradiction between precision and time consumption.
Solution Approach 2:
The patent performs preliminary actions by defining roadmaps and positioning rules for each part model before actual nesting optimization. These pre-defined constraints and pathways enable faster parallel optimization while preserving positioning accuracy, as the search space is pre-constrained to valid configurations.
2Productivity
If parallel optimization is implemented for multiple part models, then nesting efficiency improves, but system complexity and computational resources increase
Solution Approach 1:
The patent segments the nesting system into independent batch processors that work in parallel. Each batch is processed independently with its own roadmap and positioning rules, enabling parallelization without requiring complex inter-batch coordination, thus improving efficiency while controlling system complexity.
Solution Approach 2:
The patent optimizes positioning for each batch independently rather than optimizing all parts simultaneously. This partial action approach achieves sufficient nesting efficiency through parallel batches without requiring the excessive computational complexity of global simultaneous optimization.
3Quantity of substance
If more parts are nested in the printing space, then material utilization improves, but positioning constraints and collision detection become more difficult
Solution Approach 1:
The patent segments parts into batches and defines roadmaps that partition the configuration space. This segmentation reduces the complexity of constraint detection and collision verification by limiting the search to predefined pathways, enabling higher part density without proportionally increasing detection difficulty.
Solution Approach 2:
The patent performs preliminary definition of roadmaps and positioning rules that encode constraint information before optimization. This preliminary action pre-processes constraint data into actionable pathways, making constraint detection and collision verification more efficient even as part quantity increases.
Data Source
AI summary
Methods of nesting parts for 3D printing and of modularly managing the 3D printing as well as corresponding modules are provided. Methods split received part models into model batches, and repeatedly, set consecutive model batches into printing space(s) that are being gradually filled, by defining, for each part model in the model batch, a roadmap with respect to the occupied space and a set of positioning rules, and independently from the other part models in the model batch, and optimizing, in parallel for the part models in the model batch, a part positioning scheme for the model batch parts. The methods may further manage the allocation of printing spaces with respect to incoming printing requests to incorporate the respective parameters into the parameters of the nesting process. The methods exhibit a high level of process parallelization, at all levels of space and parts' allocation and nesting.