A Review on Machine Learning, Big Data Analytics, and Design for Additive Manufacturing for Aerospace Applications
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Review on Machine Learning, Big Data Analytics, and Design for Additive Manufacturing for Aerospace Applications
Authors
Keywords
-
Journal
JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-07-13
DOI
10.1007/s11665-022-07125-4
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A physics-informed machine learning model for porosity analysis in laser powder bed fusion additive manufacturing
- (2021) Rui Liu et al. The International Journal of Advanced Manufacturing Technology
- Integrated Fuzzy Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution for Additive Manufacturing Printer Selection
- (2021) Kasin Ransikarbum et al. JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
- Component-wise reduced order model lattice-type structure design
- (2021) Sean McBane et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- Machine learning based layer roughness modeling in robotic additive manufacturing
- (2021) Ahmed Yaseer et al. Journal of Manufacturing Processes
- Using machine learning to aid in the parameter optimisation process for metal-based additive manufacturing
- (2020) Cassidy Silbernagel et al. RAPID PROTOTYPING JOURNAL
- Machine Learning in Additive Manufacturing: A Review
- (2020) Lingbin Meng et al. JOM
- Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives
- (2020) YuanBin Wang et al. Science China-Technological Sciences
- Integration of hybrid additive/subtractive manufacturing planning and scheduling by metaheuristics
- (2020) Andrea Rossi et al. COMPUTERS & INDUSTRIAL ENGINEERING
- A Decision-Support Model for Additive Manufacturing Scheduling Using an Integrative Analytic Hierarchy Process and Multi-Objective Optimization
- (2020) Kasin Ransikarbum et al. Applied Sciences-Basel
- A review of topology optimization for additive manufacturing: Status and challenges
- (2020) Jihong ZHU et al. Chinese Journal of Aeronautics
- Deep Learning-Based Data Fusion Method for In Situ Porosity Detection in Laser-Based Additive Manufacturing
- (2020) Qi Tian et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- Process planning for five-axis support free additive manufacturing
- (2020) Xinyi Xiao et al. Additive Manufacturing
- A big data-driven framework for sustainable and smart additive manufacturing
- (2020) Arfan Majeed et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- An advanced fuzzy approach for modeling the yield improvement of making aircraft parts using 3D printing
- (2019) Toly Chen et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Additive manufacturing: Challenges, trends, and applications
- (2019) Osama Abdulhameed et al. Advances in Mechanical Engineering
- From Topology Optimization Design to Additive Manufacturing: Today’s Success and Tomorrow’s Roadmap
- (2019) Liang Meng et al. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
- Topology optimization of continuum structures under hybrid additive-subtractive manufacturing constraints
- (2019) Yong Sheng Han et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- An aerospace bracket designed by thermo-elastic topology optimization and manufactured by additive manufacturing
- (2019) Guanghui SHI et al. Chinese Journal of Aeronautics
- Review: The Impact of Metal Additive Manufacturing on the Aerospace Industry
- (2019) Shahir Mohd Yusuf et al. Metals
- Manufacturability analysis and process planning for additive and subtractive hybrid manufacturing of Quasi-rotational parts with columnar features
- (2019) Li Chen et al. COMPUTER-AIDED DESIGN
- Data-driven cost estimation for additive manufacturing in cybermanufacturing
- (2018) Siu L. Chan et al. JOURNAL OF MANUFACTURING SYSTEMS
- Enhanced beads overlapping model for wire and arc additive manufacturing of multi-layer multi-bead metallic parts
- (2018) Yongzhe Li et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Qualification of additively manufactured aerospace brackets: A comparison between thermoelastic stress analysis and theoretical results
- (2018) Gloria Allevi et al. MEASUREMENT
- A dimensional compensation algorithm for vertical bending deformation of 3D printed parts in selective laser sintering
- (2018) Sangho Ha et al. RAPID PROTOTYPING JOURNAL
- Current and future trends in topology optimization for additive manufacturing
- (2018) Jikai Liu et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- Laser Direct Metal Deposition of 2024 Al Alloy: Trace Geometry Prediction via Machine Learning
- (2018) Fabrizia Caiazzo et al. Materials
- Layer-wise Spatial Modeling of Porosity in Additive Manufacturing
- (2018) Jia (Peter) Liu et al. IISE Transactions
- Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment
- (2018) Grace X. Gu et al. Materials Horizons
- Effect of processing conditions on the microstructure, porosity, and mechanical properties of Ti-6Al-4V repair fabricated by directed energy deposition
- (2018) Nathan A. Kistler et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Classifying the Dimensional Variation in Additive Manufactured Parts From Laser-Scanned Three-Dimensional Point Cloud Data Using Machine Learning Approaches
- (2017) M. Samie Tootooni et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- Multi-objective optimization analysis for part-to-Printer assignment in a network of 3D fused deposition modeling
- (2017) Kasin Ransikarbum et al. JOURNAL OF MANUFACTURING SYSTEMS
- Deep quantum inspired neural network with application to aircraft fuel system fault diagnosis
- (2017) Zehai Gao et al. NEUROCOMPUTING
- A hybrid machine learning approach for additive manufacturing design feature recommendation
- (2017) Xiling Yao et al. RAPID PROTOTYPING JOURNAL
- Design for Additive Manufacturing: Trends, opportunities, considerations, and constraints
- (2016) Mary Kathryn Thompson et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Additive Manufacturing for Aerospace Flight Applications
- (2016) A. A. Shapiro et al. JOURNAL OF SPACECRAFT AND ROCKETS
- TC17 titanium alloy laser melting deposition repair process and properties
- (2016) Qi Liu et al. OPTICS AND LASER TECHNOLOGY
- Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing
- (2016) Sarah K. Everton et al. MATERIALS & DESIGN
- Topology Optimization in Aircraft and Aerospace Structures Design
- (2015) Ji-Hong Zhu et al. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
- Modeling and simulation of cooling-induced residual stresses in heated particulate mixture depositions in additive manufacturing
- (2015) T. I. Zohdi COMPUTATIONAL MECHANICS
- A new computational intelligence approach in formulation of functional relationship of open porosity of the additive manufacturing process
- (2015) A. Garg et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Measurement of environmental aspect of 3-D printing process using soft computing methods
- (2015) A. Garg et al. MEASUREMENT
- The present and future of additive manufacturing in the aerospace sector: A review of important aspects
- (2015) Adrián Uriondo et al. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING
- Vector optimization of laser solid freeform fabrication system using a hierarchical mutable smart bee-fuzzy inference system and hybrid NSGA-II/self-organizing map
- (2012) Alireza Fathi et al. JOURNAL OF INTELLIGENT MANUFACTURING
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started