Object Group Packing for Additive Manufacturing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current additive manufacturing techniques face challenges in efficiently packing 3D objects into a build volume, particularly due to the computationally intensive nature of object packing problems, which can lead to objects with lower priority being left out or manufactured at suboptimal locations, affecting quality and production efficiency.
Innovation Solution
The method involves prioritizing objects using genetic procedures to order them into groups based on sorting factors such as target region, geometrical features, timeline, object quantity, and priority input, and using a genetic algorithm to determine optimal packing arrangements within the build volume, ensuring higher priority objects are placed strategically for better manufacturing quality and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computational algorithms are used to optimize object packing arrangements, then manufacturing efficiency and quality improve, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the packing problem by dividing objects into priority groups (first priority group, second priority group, etc.) and solving packing arrangements for each group separately in sequence. This segmentation reduces the overall computational complexity by breaking down the NP-complete problem into smaller, more manageable sub-problems that can be solved more efficiently.
Solution Approach 2:
The patent applies preliminary action by pre-sorting objects into priority groups before performing the actual packing optimization. Objects are classified and ordered based on their priority levels in advance, which simplifies the subsequent packing algorithm execution and improves manufacturing efficiency by ensuring high-priority objects are placed first in optimal locations.
2Productivity
If more objects are packed into the build volume, then production output increases, but packing complexity and computational requirements increase
Solution Approach 1:
The patent segments objects into multiple priority groups and processes each group separately. This approach allows more objects to be packed into the build volume by systematically arranging them in priority order, reducing the computational burden compared to optimizing all objects simultaneously while maximizing production output.
Solution Approach 2:
The patent changes the parameter of object arrangement by introducing priority-based grouping and ordering. Instead of treating all objects equally, the system assigns priority parameters and uses these to guide the packing process, enabling more objects to be efficiently packed without exponentially increasing computational complexity.
3Manufacturing precision
If priority-based grouping is implemented, then manufacturing quality improves, but process complexity increases
Solution Approach 1:
The patent implements priority-based grouping by segmenting objects into distinct priority groups (first priority, second priority, etc.). This segmentation enables differential treatment of objects based on their importance, ensuring high-priority objects receive optimal placement first, thereby improving manufacturing quality while keeping the process complexity manageable through systematic categorization.
Solution Approach 2:
The patent applies preliminary action by pre-classifying objects into priority groups before the packing process. This preliminary classification simplifies the overall process complexity by establishing a clear hierarchy upfront, allowing the packing algorithm to focus on optimizing placements within each priority level rather than dealing with all objects equally from scratch.
Data Source
AI summary
Examples of methods for object group packings are described herein. In some examples, a method includes ordering objects of a chromosome into a first group and a second group in accordance with a first priority and a second priority. In some examples, the method includes determining, using a genetic procedure in accordance with the first priority and the second priority, a first arrangement within the first group and a second arrangement within the second group to produce a packing in a volume.