Density Rank Matrix Normalization for 3D Printing
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Solution Overview
Problem
In 3D printing, reducing material usage to achieve weight reduction and improved thermal management while maintaining structural strength and stress accommodation properties is challenging, as it often results in weakened objects.
Innovation Solution
The development of an apparatus and method for density rank matrix normalization, which generates a density threshold matrix from a density rank matrix to produce 3D objects with variable density, ensuring specified structural strength and stress accommodation properties by customizing the matrix for specific structures and printers, using techniques like blue noise structures and line dilation, and applying normalization specifications to control minimum and maximum densities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Weight of stationary object
If material usage is reduced to achieve weight reduction and improved thermal management, then weight and thermal performance are improved, but structural strength and stress accommodation properties deteriorate
Solution Approach 1:
The patent applies local quality by varying the density of material throughout the 3D printed object based on a continuous density field. Different regions of the object have different material densities - areas requiring higher strength have greater material density, while areas where weight reduction is prioritized have lower density. This is achieved through the density rank matrix normalization process that maps rank values to threshold values, creating a bistate output that preserves the density distribution characteristics of the continuous field while enabling manufacturing with discrete material deposition.
Solution Approach 2:
The patent changes the density parameter of the material throughout the object to optimize the strength-weight tradeoff. By normalizing the density rank matrix and generating threshold values from rank values, the system transforms a continuous density field into a manufacturable bistate structure. This parameter transformation allows the object to have variable density regions that accommodate both weight reduction goals and structural strength requirements in different locations.
2Weight of stationary object
If material usage is reduced to achieve weight reduction, then weight is reduced, but stress accommodation properties deteriorate
Solution Approach 1:
The patent applies local quality by varying the density of material throughout the 3D printed object based on a continuous density field. Different regions of the object have different material densities - areas requiring higher strength have greater material density, while areas where weight reduction is prioritized have lower density. This is achieved through the density rank matrix normalization process that maps rank values to threshold values, creating a bistate output that preserves the density distribution characteristics of the continuous field while enabling manufacturing with discrete material deposition.
Solution Approach 2:
The patent changes the density parameter of the material throughout the object to optimize the strength-weight tradeoff. By normalizing the density rank matrix and generating threshold values from rank values, the system transforms a continuous density field into a manufacturable bistate structure. This parameter transformation allows the object to have variable density regions that accommodate both weight reduction goals and structural strength requirements in different locations.
Data Source
AI summary
According to an example, density rank matrix normalization for three dimensional printing may include receiving a density rank matrix. The density rank matrix may include elements that include rank values, and the rank values may specify an order by which a voxel is to be turned on to generate an output object. A normalization specification of maximum and minimum structure sizes for structures that are to form the output object may be received. Further, each of the rank values may be converted, according to the normalization specification, to a corresponding threshold value to generate a density threshold matrix.