Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning
出版年份 2022 全文链接
标题
Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning
作者
关键词
Laser powder bed fusion, Porosity prediction, Meltpool monitoring, Imaging pyrometer, Physics-informed machine learning
出版物
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
Volume 304, Issue -, Pages 117550
出版商
Elsevier BV
发表日期
2022-03-10
DOI
10.1016/j.jmatprotec.2022.117550
参考文献
相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。- Toward in-situ flaw detection in laser powder bed fusion additive manufacturing through layerwise imagery and machine learning
- (2021) Zackary Snow et al. JOURNAL OF MANUFACTURING SYSTEMS
- Part-scale thermal simulation of laser powder bed fusion using graph theory: Effect of thermal history on porosity, microstructure evolution, and recoater crash
- (2021) Reza Yavari et al. MATERIALS & DESIGN
- Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm
- (2021) Shenghan Guo et al. JOURNAL OF MANUFACTURING SYSTEMS
- In situ porosity intelligent classification of selective laser melting based on coaxial monitoring and image processing
- (2021) Jingchang Li et al. MEASUREMENT
- Digitally twinned additive manufacturing: Detecting flaws in laser powder bed fusion by combining thermal simulations with in-situ meltpool sensor data
- (2021) R. Yavari et al. MATERIALS & DESIGN
- Towards a generic physics-based machine learning model for geometry invariant thermal history prediction in additive manufacturing
- (2021) Kari Lovise Ness et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Mechanistic artificial intelligence (mechanistic-AI) for modeling, design, and control of advanced manufacturing processes: Current state and perspectives
- (2021) Mojtaba Mozaffar et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Correlating in-situ sensor data to defect locations and part quality for additively manufactured parts using machine learning
- (2021) Zackary Snow et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Machine Learning in Additive Manufacturing: A Review
- (2020) Lingbin Meng et al. JOM
- Computational Assessment of Thermokinetics and Associated Microstructural Evolution in Laser Powder Bed Fusion Manufacturing of Ti6Al4V Alloy
- (2020) Mangesh V. Pantawane et al. Scientific Reports
- Revealing relationships between porosity, microstructure and mechanical properties of laser powder bed fusion 316L stainless steel through heat treatment
- (2020) Tobias Ronneberg et al. MATERIALS & DESIGN
- Processing parameters in laser powder bed fusion metal additive manufacturing
- (2020) J.P. Oliveira et al. MATERIALS & DESIGN
- Neural network based image segmentation for spatter extraction during laser-based powder bed fusion processing
- (2020) Zhenbiao Tan et al. OPTICS AND LASER TECHNOLOGY
- Optimisation of process parameters for an additively manufactured AlSi10Mg alloy: Limitations of the energy density-based approach on porosity and mechanical properties estimation
- (2020) Maverick Giovagnoli et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- A three-phase model for simulation of heat transfer and melt pool behaviour in laser powder bed fusion process
- (2020) E.L. Li et al. POWDER TECHNOLOGY
- Identification and characterization of spatter particles and their effect on surface roughness, density and mechanical response of 17-4 PH stainless steel laser powder-bed fusion parts
- (2019) Usman Ali et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Revisiting fundamental welding concepts to improve additive manufacturing: From theory to practice
- (2019) J.P. Oliveira et al. PROGRESS IN MATERIALS SCIENCE
- In-process monitoring of porosity in additive manufacturing using optical emission spectroscopy
- (2019) Mohammad Montazeri et al. IISE Transactions
- Additive manufacturing of metallic components – Process, structure and properties
- (2018) T. DebRoy et al. PROGRESS IN MATERIALS SCIENCE
- Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring
- (2018) Yingjie Zhang et al. MATERIALS & DESIGN
- In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks
- (2018) Dongsen Ye et al. ISA TRANSACTIONS
- A deep neural network for classification of melt-pool images in metal additive manufacturing
- (2018) Ohyung Kwon et al. JOURNAL OF INTELLIGENT MANUFACTURING
- On the effect of spatter particles distribution on the quality of Hastelloy X parts made by laser powder-bed fusion additive manufacturing
- (2018) Reza Esmaeilizadeh et al. Journal of Manufacturing Processes
- A statistical learning method for image-based monitoring of the plume signature in laser powder bed fusion
- (2018) M. Grasso et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Additive manufacturing of fatigue resistant materials: Challenges and opportunities
- (2017) Aref Yadollahi et al. INTERNATIONAL JOURNAL OF FATIGUE
- Additive manufacturing in the context of structural integrity
- (2017) Michael Gorelik INTERNATIONAL JOURNAL OF FATIGUE
- Process defects andin situmonitoring methods in metal powder bed fusion: a review
- (2017) Marco Grasso et al. MEASUREMENT SCIENCE and TECHNOLOGY
- On the limitations of Volumetric Energy Density as a design parameter for Selective Laser Melting
- (2017) Umberto Scipioni Bertoli et al. MATERIALS & DESIGN
- Metal vapor micro-jet controls material redistribution in laser powder bed fusion additive manufacturing
- (2017) Sonny Ly et al. Scientific Reports
- Laser powder-bed fusion additive manufacturing: Physics of complex melt flow and formation mechanisms of pores, spatter, and denudation zones
- (2016) Saad A. Khairallah et al. ACTA MATERIALIA
- Metal Additive Manufacturing: A Review of Mechanical Properties
- (2016) John J. Lewandowski et al. Annual Review of Materials Research
- A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes
- (2016) Mahesh Mani et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- The metallurgy and processing science of metal additive manufacturing
- (2016) W. J. Sames et al. INTERNATIONAL MATERIALS REVIEWS
- Overview of Materials Qualification Needs for Metal Additive Manufacturing
- (2016) Mohsen Seifi et al. JOM
- Reducing lack of fusion during selective laser melting of CoCrMo alloy: Effect of laser power on geometrical features of tracks
- (2016) K. Darvish et al. MATERIALS & DESIGN
- Correlation between porosity and processing parameters in TiAl6V4 produced by selective laser melting
- (2016) Galina Kasperovich et al. MATERIALS & DESIGN
- Review of in-situ process monitoring and in-situ metrology for metal additive manufacturing
- (2016) Sarah K. Everton et al. MATERIALS & DESIGN
- On the role of melt flow into the surface structure and porosity development during selective laser melting
- (2015) Chunlei Qiu et al. ACTA MATERIALIA
- In situ quality control of the selective laser melting process using a high-speed, real-time melt pool monitoring system
- (2014) S. Clijsters et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Density of additively-manufactured, 316L SS parts using laser powder-bed fusion at powers up to 400 W
- (2014) Chandrika Kamath et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Observation of keyhole-mode laser melting in laser powder-bed fusion additive manufacturing
- (2014) Wayne E. King et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Overview of modelling and simulation of metal powder bed fusion process at Lawrence Livermore National Laboratory
- (2014) W. King et al. MATERIALS SCIENCE AND TECHNOLOGY
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now