Multiscale Modeling of a Chain Comprising Selective Laser Melting and Post-Machining toward Nanoscale Surface Finish

Area of Science:

• Materials Science
• Manufacturing Engineering
• Surface Engineering

Background:

• Selective laser melting (SLM) inherently produces rough surfaces, necessitating post-processing for improved performance.
• Optimizing surface finish requires integrated simulation of additive manufacturing and post-processing techniques.
• Current models often lack a comprehensive approach to predict surface roughness evolution through multi-step treatments.

Purpose of the Study:

• To develop and validate an integrated simulation framework for predicting surface roughness.
• To model the sequential effects of SLM, milling, and surface burnishing on surface roughness.
• To optimize the post-processing chain for achieving superior surface finish and manufacturing efficiency.

Main Methods:

• Developed a simulation framework incorporating closed-form analytical solutions for SLM, milling, and burnishing.
• Sequentially linked the processes, using the output of one as the input for the next.
• Validated simulation predictions against measured arithmetic surface roughness values.

Main Results:

• Demonstrated close agreement between predicted and measured surface roughness for SLM and post-processed materials.
• Achieved nanoscale surface finish using finishing milling and single-pass rolling at 1500 N.
• Simulations revealed that omitting milling significantly increases production time and rolling force requirements.

Conclusions:

• The integrated simulation framework accurately predicts surface roughness changes across sequential post-processing steps.
• Finishing milling followed by surface burnishing is effective for achieving nanoscale surface finishes on SLM parts.
• Including milling in the post-processing chain enhances efficiency, reducing overall production time and required forces.