Additive Manufacturing Parameter Optimization for Anisotropic Strength

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing additive manufacturing (AM) processes struggle to consistently produce 3D objects with desired anisotropic mechanical and structural properties in non-primary directions due to a lack of objective information on parameter relationships, leading to inefficiencies in material consumption and production costs.

Innovation Solution

A design manager system that determines additive manufacturing configurations (AMCs) based on anisotropic mechanical and structural requirements, using artificial intelligence and machine learning to optimize parameters such as material type, infill density, and layer thickness, ensuring compliance with specified mechanical properties across various axes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If parameters are selected based on human experience and intuition, then primary mechanical properties may be satisfied, but non-primary mechanical properties cannot be consistently optimized and material waste increases

Engineering Contradiction:

Improvemechanical properties in non-primary directionsVSAvoidmaterial consumption

Core Design Contradiction:

Manufacturing precisionVSLoss of substance

Solution Approach 1:

The patent applies parameter changes by systematically varying AM process parameters (infill density, infill geometry, layer thickness, orientation angles) to optimize both primary and non-primary mechanical properties. The system evaluates multiple parameter combinations and selects optimal settings based on predicted mechanical performance, moving beyond fixed parameter selection to dynamic optimization.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements preliminary action through computational prediction of mechanical properties before actual manufacturing. The system uses models to forecast how different parameter combinations will affect mechanical properties in various directions, allowing parameter optimization to occur in the design phase rather than through trial-and-error manufacturing.

Inventive Principle:

Principle #10Preliminary action

2Strength

If higher infill density is used to improve mechanical properties in all directions, then structural strength increases, but manufacturing time and material consumption increase

Engineering Contradiction:

Improvemechanical strength in non-primary directionsVSAvoidmanufacturing time

Core Design Contradiction:

StrengthVSProductivity

Solution Approach 1:

The patent applies local quality by optimizing infill parameters specifically for non-primary directions where mechanical properties are typically deficient. Rather than uniformly increasing infill density throughout the entire structure, the system identifies specific regions and orientation angles that require enhanced mechanical properties and applies targeted parameter adjustments only where needed.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent implements partial action by applying enhanced infill parameters only in specific orientations and regions where non-primary mechanical properties are insufficient, rather than applying high infill density universally. This allows mechanical strength to be improved in critical directions while maintaining lower material consumption and faster manufacturing in less critical areas.

Inventive Principle:

Principle #16Partial or excessive action

3Manufacturing precision

If complex parameter optimization is performed to satisfy non-primary mechanical requirements, then mechanical precision improves, but process complexity and computational requirements increase

Engineering Contradiction:

Improveconsistency of mechanical propertiesVSAvoidparameter selection system complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent replaces complex manual parameter optimization with computational models and algorithms. The system uses software-based prediction tools that automatically evaluate multiple parameter combinations and recommend optimal settings, substituting human expert judgment and iterative physical testing with automated computational analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates virtual models and simulations of the additive manufacturing process and mechanical testing. Instead of physically manufacturing multiple test samples to determine optimal parameters, the system uses computational copies (digital twins) to predict mechanical properties and optimize parameters in a virtual environment before actual manufacturing.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS12459207B2Systems and methods for managing additive manufacturing

Publication Date: 2025.11.04 BATTELLE ENERGY ALLIANCE LLC

AI summary

A system for managing additive manufacturing (AM) may comprise a datastore configured to store entries pertaining to a design for a three-dimensional (3D) object. The entries may be configured to include a respective set of parameters for an AM process. The parameters may be configured to cause an AM system to produce 3D objects having anisotropic mechanical properties that satisfy specified anisotropic mechanical requirements. The system may further comprise a design manager configured to determine a set of parameters that optimally satisfy the specified requirements, e.g., satisfy the requirements at a minimal cost.