Research on the printing quality of large-layer thick laser selective melting of stainless steel powder

Selective laser melting (SLM) offers geometric flexibility, high resolution, and refined microstructures, yet its industrial adoption is limited by low productivity. Increasing layer thickness has shown potential to significantly improve build rates, but a systematic understanding of the interrelationships among layer thickness, powder size, process parameters, microstructural evolution, and mechanical properties remains insufficient. This study systematically evaluates 316L stainless steel processed using powder sizes of 15–53 μm and 48–105 μm under layer thicknesses of 50, 70, 90, and 110 μm. Results show relative densities exceeding 99% for layers up to 90 μm. While coarse powder at 50 μm exhibited comparable strength and slightly higher elongation than fine powder, increased lack-of-fusion defects at higher layer thicknesses led to progressive mechanical deterioration. Notably, fine powder samples at 70 μm achieved a yield strength of 592 MPa, tensile strength of 730 MPa, elongation of 60.5%, and a build rate of 7.3 mm 3 /s, demonstrating balanced properties and approximately triple the productivity compared to standard 30 μm layers. These findings suggest that a 70 μm layer thickness provides a viable trade-off between mechanical performance and build efficiency for applications not requiring high surface quality.

Authors

Institutions

Publication Details

Journal
Powder Metallurgy
Published
2026-03-13
DOI
https://doi.org/10.1177/00325899251389515
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the printing quality of large-layer thick laser selective melting of stainless steel powder

X. H. Li, Weiwei Li, Shuhuan Wang, Dingguo Zhao et al.
Powder Metallurgy
Additive Manufacturing Materials and Processes
article

Research on the printing quality of large-layer thick laser selective melting of stainless steel powder

X. H. Li, Weiwei Li, Shuhuan Wang, Dingguo Zhao, Yan Liu
article en

Abstract

Selective laser melting (SLM) offers geometric flexibility, high resolution, and refined microstructures, yet its industrial adoption is limited by low productivity. Increasing layer thickness has shown potential to significantly improve build rates, but a systematic understanding of the interrelationships among layer thickness, powder size, process parameters, microstructural evolution, and mechanical properties remains insufficient. This study systematically evaluates 316L stainless steel processed using powder sizes of 15–53 μm and 48–105 μm under layer thicknesses of 50, 70, 90, and 110 μm. Results show relative densities exceeding 99% for layers up to 90 μm. While coarse powder at 50 μm exhibited comparable strength and slightly higher elongation than fine powder, increased lack-of-fusion defects at higher layer thicknesses led to progressive mechanical deterioration. Notably, fine powder samples at 70 μm achieved a yield strength of 592 MPa, tensile strength of 730 MPa, elongation of 60.5%, and a build rate of 7.3 mm 3 /s, demonstrating balanced properties and approximately triple the productivity compared to standard 30 μm layers. These findings suggest that a 70 μm layer thickness provides a viable trade-off between mechanical performance and build efficiency for applications not requiring high surface quality.

Powder Metallurgy
North China University of Science and Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Additive Manufacturing Materials and Processes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.