Article
Chemistry, Physical
Leonardo Hernandez-Flores, Angel-Ivan Garcia-Moreno, Enrique Martinez-Franco, Guillermo Ronquillo-Lomeli, Jhon Alexander Villada-Villalobos
Summary: Heat treatment of metals can alter their microstructure and properties, and temperature-time-transformation diagrams are important for interpreting the resulting microstructures. This study proposes a novel approach using artificial neural networks to predict TTT diagrams for a nickel-aluminum alloy, and the accuracy of the method is validated.
Article
Computer Science, Interdisciplinary Applications
Yosep Oh, Michael Sharp, Timothy Sprock, Soonjo Kwon
Summary: "Additive manufacturing (AM) has introduced significant changes to traditional manufacturing with the possibility of accurate build time estimation using neural networks (NNs), particularly convolutional NNs (CNNs). This study aims to fill the gap in performance comparison for build time estimation among different NN types. Computational experiments show that CNN-based estimation is often more accurate and strongly influenced by design factors, such as changing the size of 3D models."
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2021)
Article
Engineering, Manufacturing
Amanda Rossi de Oliveira, Vitor Furlan de Oliveira, Julio Carlos Teixeira, Erik Gustavo Del Conte
Summary: This study investigated the magnetic properties and residual stress of maraging steel 300 specimens built by PBF in three different orientations. The results showed that build orientations in the PBF process can affect magnetic properties and residual stresses of the material, with Barkhausen Noise being a potential method for residual stress inspection and quality management improvement.
ADDITIVE MANUFACTURING
(2021)
Review
Chemistry, Physical
Muhammad Arif Mahmood, Anita Ioana Visan, Carmen Ristoscu, Ion N. Mihailescu
Summary: The application of machine learning technology, particularly the use of artificial neural network models, shows great potential in the field of 3D printing due to its ability to handle large datasets and strong computational power.
Article
Nanoscience & Nanotechnology
Dingcheng Tang, Xiaofan He, Bin Wu, Linwei Dang, Hao Xin, Yuhai Li
Summary: This paper investigates the effects of build orientation on the anisotropic fatigue performance of DED Ti-6Al-4V, and reveals through fatigue tests and microstructure analysis that crystallographic orientation and α colony are the key factors causing the anisotropy induced by build orientation.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2023)
Article
Engineering, Manufacturing
Marton Tamas Birosz, Ferenc Safranyik, Matyas Ando
Summary: Additive Manufacturing technology can improve the dimensional accuracy, surface quality, and mechanical properties of parts by choosing the right printing orientation. An algorithm has been developed to determine the optimal build orientation for a given load case, leading to enhanced mechanical performance.
JOURNAL OF MANUFACTURING PROCESSES
(2022)
Article
Automation & Control Systems
Marina A. Matos, Ana Maria A. C. Rocha, Lino A. Costa
Summary: In this paper, a many-objective approach is applied to optimize four conflicting objective functions regarding 3D object build orientation using the NSGA-II algorithm. By performing bi-objective and many-objective optimization, more optimal solutions are identified for decision-makers to choose from based on their preferences. Visualization tools are used to inspect relationships and trade-offs between objectives, confirming the effectiveness of the proposed approach.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Engineering, Multidisciplinary
E. Hosseini, P. Gh Ghanbari, R. Molinaro, S. Mishra
Summary: This study explores the application of physics informed neural networks (PINNs) as a low-cost physics-based simulation approach for the thermal analysis of the laser powder bed fusion (LPBF) process. PINNs solve the heat transfer equation parametrically and provide reliable transient and steady-state temperature profiles for single-track LPBF depositions. The trained PINNs can calculate temperature profiles and melt-pool dimensions during the LPBF process with practically zero computational cost. The reliability of PINNs outcomes is verified through ground-truth data based on benchmark finite element simulations.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Materials Science, Multidisciplinary
G. Moeini, S. Sajadifar, T. Wegener, C. Roessler, A. Gerber, S. Boehm, T. Niendorf
Summary: This study investigated the friction stir welding of additive manufactured components, analyzing the microstructural and mechanical property changes in the friction stir zone. Different build orientations had a significant impact on the tensile strength of the welded joints. Under low-cycle fatigue conditions, parts with building direction parallel to the loading direction showed superior fatigue performance.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2021)
Article
Automation & Control Systems
Rahul Ramachandran, Gurunathan Saravana Kumar
Summary: This paper evaluates the correlation coefficient and computational cost of different build time estimate models and proposes a hybrid optimization framework using multifidelity models to obtain optimized build orientation. The proposed method is demonstrated with example case studies and compared to a standard optimization algorithm, showcasing its overall methodology and effectiveness.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Automation & Control Systems
Rahul Ramachandran, Gurunathan Saravana Kumar
Summary: Build time estimation is crucial for the fused filament fabrication (FFF) process. This paper evaluates and benchmarks different build time estimation models in relation to a validated high-fidelity model. It then proposes a hybrid optimization framework that uses multifidelity models to improve computational performance and obtain optimum build orientation.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Chemistry, Physical
Mostafa Omran Hussein, Lamis Ahmed Hussein
Summary: This study aimed to find the optimal 3D printing parameters, including build angle and support structures' diameter, for removable partial denture (RPD) frameworks. The results showed that a build angle of 150 degrees and thin diameter support structures achieved the best accuracy and time-saving.
Article
Engineering, Manufacturing
Siqi Chen, Yuexin Yang, Shuai Liu, Molong Duan
Summary: This paper presents a method to improve the deposition accuracy of additive manufacturing systems using real-time thermal images. By capturing and compensating for the geometrical accuracy of printed parts and establishing the relationship between inaccuracy and deposition trajectory commands, deposition accuracy can be enhanced.
ADDITIVE MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Mohammad Reza Rezaei, Mahmoud Houshmand, Omid Fatahi Valilai
Summary: In Industry 4.0, intelligent cloud-based additive manufacturing is crucial, but integrating it with service-oriented manufacturing faces challenges due to the lack of necessary frameworks.
PEERJ COMPUTER SCIENCE
(2021)
Article
Automation & Control Systems
Reza Karimzadeh, Mohsen Hamedi
Summary: This paper proposes a topology optimization algorithm based on the SIMP method, which combines data clustering and neural networks to enhance sensitivity analysis, capable of generating a support-free part design with desirable compliance. The experimental results demonstrate promising savings in material usage and manufacturing time.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)