Article
Engineering, Chemical
Erlei Li, Zongyan Zhou, Lin Wang, Qijun Zheng, Ruiping Zou, Aibing Yu
Summary: This study investigated the multi-physics interactions between scanning tracks in laser powder bed fusion (LPBF) using a CFD-based model. The results showed that the flow at the head of the first track gradually changed due to the intense centrifugal motion of the second track, causing the combined tracks to spread. The voids between adjacent tracks were compressed by the molten liquid and sealed by the resolidified part, resulting in large pores, especially for medium laser power and hatch space. The liquid phase overlap of unidirectional track was narrower compared to bidirectional scanning. Under the island scanning strategy, the flow direction of the molten liquid changed multiple times and pores tended to be eliminated. This study contributes to a better understanding of the physics involved in the LPBF process.
Article
Engineering, Industrial
Yangyiwei Yang, Alexander Grossmann, Patrick Kuehn, Jan Moelleney, Lorenz Kropholler, Christian Mittelstedt, Bai-Xiang Xu
Summary: This study derives an improved dimensionless scaling law based on dimensional analysis to characterize the melt pool width in LPBF process, which shows good correlation in validation. The law, after validation, can be extended to a unified law for different beam sizes, suitable for designing and producing thin-walled components with strut thicknesses in the micrometer range.
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
(2022)
Article
Engineering, Industrial
Tatsuaki Furumoto, Kazushi Oishi, Satoshi Abe, Kotaro Tsubouchi, Mitsugu Yamaguchi, Adam T. Clare
Summary: This study investigates the dynamic temperature behavior around a melt pool in metal-based powder bed fusion using a laser beam. The temperature distribution of the melt pool is influenced by morphological changes of the metal powder, causing asymmetric temperature distribution. Factors such as droplet cohesion, remaining heat energy, and heat conduction inside the melt pool play significant roles.
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
(2022)
Article
Engineering, Industrial
Jaehyuk Kim, Zhuo Yang, Hyunwoong Ko, Hyunbo Cho, Yan Lu
Summary: The paper proposes a novel deep learning-based methodology to estimate the melt pool positions in the machine-build coordinate system directly. It combines image preprocessing, convolutional neural network, and Kalman filtering to achieve accurate estimation of melt pool positions.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Mechanical
Qisheng Wang, Xin Lin, Xianyin Duan, Ruqiang Yan, Jerry Ying Hsi Fuh, Kunpeng Zhu
Summary: Laser powder bed fusion (L-PBF) is a metal additive manufacturing process with potential for high-performance metal components. However, stability and repeatability issues limit its industrial application. To ensure product quality, process monitoring and control are crucial. A new motion feature is extracted and a classification model is constructed to identify the changing melt pool states during the L-PBF process. The Gaussian process classification (GPC) model achieves better recognition results compared to other models, with an overall recognition rate of 87.1%.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Automation & Control Systems
Juan Trejos-Taborda, Luis Reyes-Osorio, Carlos Garza, Patricia del Carmen Zambrano-Robledo, Omar Lopez-Botello
Summary: A numerical model of laser powder bed fusion (LPBF) was developed to study the behavior of melt pool dynamics. The results showed that melt pool dimensions follow a thermal pattern, and a new criterion was proposed to accurately predict the dimensions.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Automation & Control Systems
Sepehr Fathizadan, Feng Ju, Yan Lu, Zhuo Yang
Summary: Parametric and regression-based anomaly detection methods are not effective for high-dimensional and spatio-temporally correlated data. Model agnostic deep learning methods are gaining popularity due to recent advancements in high-performance computing technologies. This study proposes a configuration of convolutional long short term memory auto-encoders and clustering algorithm for deep spatio-temporal representation learning from melt pool images in experimental additive manufacturing. The proposed method achieves high accuracy and low false alarm rate in various additive manufacturing process scenarios.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Manufacturing
Junhao Zhao, Binbin Wang, Tong Liu, Liangshun Luo, Yanan Wang, Xiaonan Zheng, Liang Wang, Yanqing Su, Jingjie Guo, Hengzhi Fu, Dayong Chen
Summary: This paper establishes a novel reconstruction model for melt pool overlapping in laser powder bed fusion and investigates its effects on elemental losses, defect formation, and microstructure evolution. It is found that the loss of elements with low boiling points is positively correlated with the number of melting cycles, incomplete defects are formed in regions melted less than twice, and hole defects are found predominantly in regions melted more than six times. The fine-grained area tends to vary with both melt pool overlapping and heat accumulation, and an increase in sample temperature due to overlapping can augment the number and size of precipitates. This work offers a new way to improve the microstructure and mechanical properties of materials by optimizing overlapping conditions.
ADDITIVE MANUFACTURING
(2022)
Article
Materials Science, Multidisciplinary
I. Rosenthal, J. S. Weaver, S. Moylan
Summary: This investigation explores the influence of melt pool structure on a Nickel superalloy 625 in additive manufacturing. Different laser parameters and build orientations were used to build samples, which were systematically characterized and mechanically tested. The investigation reveals that the melt pool structure directly affects properties such as fracture pathways and elongation, and interactions between built layers and tensile direction were observed.
MATERIALS TODAY COMMUNICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Benjamin Meier, Fernando Warchomicka, Daniela Ehgartner, Denis Schuetz, Paul Angerer, Jaroslaw Wosik, Carlos Belei, Jelena Petrusa, Reinhard Kaindl, Wolfgang Waldhauser, Christof Sommitsch
Summary: Titanium alloy Ti6Al4V is commonly used due to its high strength, ductility, corrosion resistance, and weldability. This study shows that the powder of this alloy can be reused, but it picks up oxygen after each cycle, forming an oxide layer that affects its optical and thermal properties, as well as laser absorption and melt pool properties. The results indicate that the powder can be reused up to 18 cycles without affecting the tensile properties, but it causes a decrement in impact strength.
SUSTAINABLE MATERIALS AND TECHNOLOGIES
(2023)
Article
Thermodynamics
Heng Ma, Zhuangzhuang Mao, Wei Feng, Yang Yang, Ce Hao, Jiangfan Zhou, Sheng Liu, Huimin Xie, Guangping Guo, Zhanwei Liu
Summary: In this study, a coaxial temperature measurement system based on dual-wavelength thermometry is developed for the in-situ measurement and monitoring of melt pool characteristics in metal additive manufacturing. Experimental validation shows that the temperature measuring error of the system is less than 1%. The temperature distribution, profile, temperature gradient, and cooling rate of the melt pool are measured and analyzed, revealing the significant impact of linear energy density on the melt pool temperature. Optimized parameters minimize the fluctuation of melt pool temperature and promote the production of high-quality parts.
APPLIED THERMAL ENGINEERING
(2022)
Article
Engineering, Mechanical
Arash Soltani-Tehrani, Rakish Shrestha, Nam Phan, Mohsen Seifi, Nima Shamsaei
Summary: The study shows that altering scanning speed can impact the melt pool characteristics of LB-PBF stainless steel parts, reducing volumetric defects, particularly lack of fusion. Adjusting scanning speed to achieve similar melt pool characteristics under the same manufacturing process parameters can result in parts with similar porosity, consequently affecting fatigue life.
INTERNATIONAL JOURNAL OF FATIGUE
(2021)
Article
Engineering, Manufacturing
Dominik Kozjek, Fred M. Carter, Conor Porter, Jon-Erik Mogonye, Kornel Ehmann, Jian Cao
Summary: This study developed a machine learning-based predictive model to reduce the uncontrolled process variability in laser powder bed fusion. By measuring the melt pool temperature with high resolution and training the model based on previous data, the model can predict the melt pool temperatures for the next layer. The study provides guidelines for feature vector design and selection, and evaluates the performance of the model using real physical data.
JOURNAL OF MANUFACTURING PROCESSES
(2022)
Article
Thermodynamics
Mehmet Mollamahmutoglu, Oguzhan Yilmaz
Summary: Laser-based powder bed fusion is a widely used additive manufacturing method with unique melt pool characteristics and various physical phenomena. Volumetric heat sources are commonly used for simplifying modeling and reducing calculation costs, but they may contain non-standard parameters and sometimes produce unreasonable results.
THERMAL SCIENCE AND ENGINEERING PROGRESS
(2021)
Review
Engineering, Chemical
Erlei Li, Zongyan Zhou, Lin Wang, Ruiping Zou, Aibing Yu
Summary: This paper provides a review of the multi-physics problems involved in laser powder bed fusion (LPBF), including metal powder recoating, melting and solidification processes. The applications of discrete element method and computational fluid dynamics in studying these processes are discussed.
Article
Nanoscience & Nanotechnology
Ankur K. Agrawal, Aparna Singh
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2017)
Article
Materials Science, Multidisciplinary
Ankur Kumar Agrawal, Aparna Singh, Anupam Vivek, Steve Hansen, Glenn Daehn
Article
Nanoscience & Nanotechnology
Ankur Kumar Agrawal, Gabriel Meric de Bellefon, Dan Thoma
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2020)
Proceedings Paper
Green & Sustainable Science & Technology
Umang Desai, Sudharm Rathore, Ankur Kumar Agarwal, Aparna Singh
2018 IEEE 7TH WORLD CONFERENCE ON PHOTOVOLTAIC ENERGY CONVERSION (WCPEC) (A JOINT CONFERENCE OF 45TH IEEE PVSC, 28TH PVSEC & 34TH EU PVSEC)
(2018)