Article
Engineering, Manufacturing
Zhiheng Hu, Yang Qi, Balasubramanian Nagarajan, Xiaojia Nie, Hu Zhang, Haihong Zhu, Xiaoyan Zeng
Summary: Selective laser melting (SLM) is a powder bed based additive manufacturing technology expected to fabricate complex parts. This study systematically investigated the evolution of top surface roughness during SLM of an Al-Cu alloy, revealing that fluid flow intensity and molten pool overlapping affect surface roughness, with increases in layer number contributing to spreading of the molten pool but also harming top surface quality with increased powder thickness.
JOURNAL OF MANUFACTURING PROCESSES
(2021)
Article
Polymer Science
Riccardo Tonello, Knut Conradsen, David Bue Pedersen, Jeppe Revall Frisvad
Summary: Selective laser sintering (SLS) is a well-established additive manufacturing technology. Efforts have been made to improve SLS by optimizing powder deposition, laser parameters, and temperature settings. This study evaluated the surface roughness and grain size differences of curved objects manufactured using a new SLS technology featuring two CO laser sources. Significant differences were found in some surface roughness and grain size measurements when varying build setup, presence of thin walls, and sample position on the powder bed.
Article
Engineering, Manufacturing
Jino Joshy, Allan George, Basil Kuriachen, Jose Mathew
Summary: This study compares the machinability characteristics of cast and SLM produced AlSi10 Mg samples and their effects after heat treatment. The results show that SLM manufactured samples have increased thrust force and cutting force compared to cast samples, but heat treatment can reduce these forces.
MATERIALS AND MANUFACTURING PROCESSES
(2023)
Article
Nanoscience & Nanotechnology
J. Karimi, C. Suryanarayana, I Okulov, K. G. Prashanth
Summary: This study investigated the effect of remelting on the microstructure and mechanical properties of Ti6Al4V materials fabricated using selective laser melting. The results showed that the number of remeltings significantly influenced the homogenization of the microstructure and mechanical properties of the materials, with an increase in hardness and ultimate tensile strength but a decrease in ductility observed with a higher number of melting steps.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Filippo Simoni, Andrea Huxol, Franz-Josef Villmer
Summary: This research focuses on achieving cost and operational benefits, particularly in the field of tool making for injection molding, by combining traditional and additive manufacturing processes. Special attention is given to optimizing surface quality, with laser remelting shown to considerably improve the surface quality of SLM parts.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Chemistry, Multidisciplinary
I. I. Cuesta, A. Diaz, M. A. Rojo, L. B. Peral, J. Martinez, J. M. Alegre
Summary: Additive manufacturing of metallic materials is widely used in various sectors. In order to ensure reliable performance of parts, it is necessary to study the effect of additive manufacturing on mechanical properties. This paper focuses on the application of Selective Laser Melting technology in the automotive industry and aims to optimize key parameters in the printing process to obtain parts with good resistance.
APPLIED SCIENCES-BASEL
(2022)
Article
Materials Science, Multidisciplinary
Sijia Liu, Minsuk Lee, Cheol Choi, Keesam Shin
Summary: In this study, the microstructure, microhardness, and porosity of additive manufactured parts fabricated by selective laser melting are investigated. The porosity of the finished product depends primarily on the energy density used and is more strongly influenced by the scanning speed than the applied laser power. The microstructure exhibits characteristic features attributed to different cooling rates near and far from the laser melting zone.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2023)
Article
Engineering, Electrical & Electronic
Ruoxin Wang, Chi Fai Cheung, Chunjin Wang
Summary: In this article, an unsupervised segmentation method is proposed to detect defects on additive manufactured surfaces, which only requires a single scanned image. The proposed method has three modules responsible for feature learning, global feature capturing, and cluster labeling. Experimental results show that the proposed method effectively segments surface defects compared to other state-of-the-art models.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Automation & Control Systems
Ebubekir Koc, Sultan Zeybek, Burcin Ozbay Kisasoz, Cemal Irfan Caliskan, Mustafa Enes Bulduk
Summary: This study presents a novel classification model based on Deep Neural Networks to estimate surface roughness for additive manufacturing. The proposed model focuses on selective laser sintering (SLS) technology and can accurately classify the surface roughness. The results show that the model outperforms other machine learning methods in classifying the surface roughness successfully on the test set.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Materials Science, Coatings & Films
Brodan Richter, Tim Radel, Frank E. Pfefferkorn
Summary: Poor fatigue life caused by rough and irregular surfaces is a significant challenge for additive manufacturing. Laser polishing, using a laser to irradiate, melt, and smooth the surface, is a solution. This study examines the laser polishing of cobalt-chromium samples produced through laser powder bed fusion. The influence of various laser processing parameters on surface smoothing is analyzed, with laser power playing the most important role. The starting surface condition and variability caused by particle adherence are also discussed. This work provides an important overview of processing aspects for advancing the commercialization of additive manufacturing technology in part finishing.
SURFACE & COATINGS TECHNOLOGY
(2022)
Article
Chemistry, Physical
Elisabeth Guenther, Moritz Kahlert, Malte Vollmer, Thomas Niendorf, Christian Greiner
Summary: The study investigated the friction performance of AISI H13 steel samples additively manufactured by laser powder bed fusion. Results showed that grinding and polishing resulted in the lowest friction coefficient, while polishing alone and laser-surface texturing increased the friction coefficient. Wear was minimal in all cases.
Article
Materials Science, Multidisciplinary
Jiapeng Sun, Qisheng Sun, Ying Liu, Bangjun Li, Zheng Zhang, Bingqian Xu, Songsong Xu, Ying Han, Yanxin Qiao, Jing Han, Guosong Wu, Paul K. Chu
Summary: The study investigates the use of ultrasonic severe surface rolling (USSR) to enhance the corrosion resistance of SLM 316L stainless steel, and finds that the USSR processed samples exhibit significant improvement in corrosion resistance, attributed to the unique gradient structure and chemically homogeneous and high-quality surface.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2022)
Article
Materials Science, Multidisciplinary
P. Ashwath, M. Anthony Xavior, Andre Batako, P. Jeyapandiarajan, J. Joel
Summary: Additive Manufacturing (AM) and Selective Laser Melting (SLM) are advanced manufacturing methods widely used in the aerospace industry. Current research focuses on using SLM to fabricate Al-Si-10Mg aluminum alloy and study the effects of scanning speed and build orientation on the mechanical strength and surface finish of the components. This research is of importance for dynamic applications.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2022)
Article
Biotechnology & Applied Microbiology
Jia Lv, Wenxuan Jin, Wenhao Liu, Xiuyu Qin, Yi Feng, Junjun Bai, Zhuangzhuang Wu, Jian Li
Summary: This study investigates the relationship between pore architecture and structure performance by designing and manufacturing three types of triply periodic minimal surface (TPMS) porous scaffolds combined with four constants. The results show that different TPMS porous scaffolds have distinct characteristics in structure, mechanical property, and cell compatibility, indicating their potential applications in specific fields.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Ruoxin Wang, Chi Fai Cheung, Chunjin Wang, Mei Na Cheng
Summary: This study focuses on the distribution and count estimation of surface defects in additive manufactured components. A deep learning characterization method based on a detail-aware dilated convolutional neural network is proposed. Experimental results show that the proposed method achieves better results compared to other state-of-the-art methods.
COMPUTERS IN INDUSTRY
(2022)