Determination of the process parameters for 17-4PH stainless steel—Rosenthal, melt pool, and microstructure properties

Since the field’s founding, understanding metal additive manufacturing (AM) procedures and the composition and characteristics of the produced metallic components has come a long way. We are optimizing the microstructure and reducing defect development achieved by fine-tuning essential process parameters like laser power and scan speed, which are crucial initial steps in improving the quality and dependability of AM components. This research aims to achieve complete dense samples by effectively controlling the energy density input during the printing process, which depends entirely on the chosen printing parameters, balancing between insufficient melting and excessive melting. This study adjusted the laser power, scanning speed, and hatch spacing to create components that were as close to fully dense as possible. Using parameters derived from the Rosenthal calculation, we printed samples using 17-4 precipitation hardening (17-4PH) stainless steel. Subsequently, the printed samples were examined using an optical microscope to detect imperfections and correlate them with the specific conditions applied in each case.

Authors

Institutions

Publication Details

Journal
Journal of Micromanufacturing
Published
2025-04-24
DOI
https://doi.org/10.1177/25165984251332071
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

Determination of the process parameters for 17-4PH stainless steel—Rosenthal, melt pool, and microstructure properties

Md. Ahadul Islam Patwary, Nayem Hossain, Md Shovon Zahid, Md. Imran Hossain et al.
1 links
Journal of Micromanufacturing
Additive Manufacturing Materials and Processes
article

Determination of the process parameters for 17-4PH stainless steel—Rosenthal, melt pool, and microstructure properties

Md. Ahadul Islam Patwary, Nayem Hossain, Md Shovon Zahid, Md. Imran Hossain, Mohammad Asaduzzaman Chowdhury
article en

Abstract

Since the field’s founding, understanding metal additive manufacturing (AM) procedures and the composition and characteristics of the produced metallic components has come a long way. We are optimizing the microstructure and reducing defect development achieved by fine-tuning essential process parameters like laser power and scan speed, which are crucial initial steps in improving the quality and dependability of AM components. This research aims to achieve complete dense samples by effectively controlling the energy density input during the printing process, which depends entirely on the chosen printing parameters, balancing between insufficient melting and excessive melting. This study adjusted the laser power, scanning speed, and hatch spacing to create components that were as close to fully dense as possible. Using parameters derived from the Rosenthal calculation, we printed samples using 17-4 precipitation hardening (17-4PH) stainless steel. Subsequently, the printed samples were examined using an optical microscope to detect imperfections and correlate them with the specific conditions applied in each case.

Journal of Micromanufacturing
International University of Business Agriculture and Technology (BD), Dhaka University of Engineering & Technology (BD)
Openalex Percentile: Top 92%
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.

Determination of the process parameters for 17-4PH stainless steel—Rosenthal, melt pool, and microstructure properties — Md. Ahadul Islam Patwary, Nayem Hossain, et al. · Journal of Micromanufacturing (2025) | TGRS Research Map | TGRS