Additive Manufacturing Optimization of any Build Issue at Any Scale

Additive Manufacturing Optimization of Any Thermal or Mechanical Build Issue at Any Scale

Adjoint sensitivity driven optimization enables fast physics based optimization for large scale additive parts. Any model input can be optimized.

Thermal Dwell Optimization

Why Delays?

Dwell optimization enables users to target delays to prevent overheating issues without adding unnecessary build time

As an added benefit, this kind of optimization is the easiest to certify, as the process parameters are unchanged

Inter-Pass Dwell Optimization for DED

Feed Forward DED thermal Management

Dwell optimization now supports part scale DED simulation, enabling users to accurately predict and optimize the temperature between DED deposition layers

Power Optimization (Beta)

Part Scale Power Optimization

PanX can optimize the laser power over the entire part volume.

This results in uniform melt pool characteristics, improving part quality and reducing porosity.

Since this is a feed forward approach, the parameters are fixed prior to the build, which is easier to qualify.

Presentation given at RAPID+TCT 2024 available here

Support Structure Optimization (Alpha)

Interlayer Temperature Optimized Support Structure

PanX uses adjoint sensitivities to drive support structure optimization.

The criteria in this example is to keep interlayer temperatures below a target threshold, while using minimal support material

This optimization converged after 8 iterations, taking only 31 seconds on an 8 core laptop

Recoater Clearance Optimized Support Structure

The criteria in this example is to keep interlayer recoater clearance risk below a target threshold, while using minimal support material

Note that the recoater clearance actually risk decreases

This optimization took 8 minutes to converge on an 8 core laptop