Semi-supervised machine learning of optical in-situ monitoring data for anomaly detection in laser powder bed fusion

References

• Abdelrahman, Mostafa, Edward W Reutzel, Abdalla R Nassar, and Thomas L Starr. 2017. “Flaw Detection in Powder Bed Fusion Using Optical Imaging.” Additive Manufacturing 15: 1–11.
   Web of Science ®Google Scholar
• Alloghani, Mohamed, Dhiya Al-Jumeily, Jamila Mustafina, Abir Hussain, and Ahmed J. Aljaaf. 2020. “A Systematic Review on Supervised and Unsupervised Machine Learning Algorithms for Data Science.” In Supervised and Unsupervised Learning for Data Science. Unsupervised and Semi-Supervised Learning, edited by M. Berry, A. Mohamed, and B. Yap, 3–21. Cham: Springer. https://doi.org/10.1007/978-3-030-22475-2_1.
   Google Scholar
• Aoyagi, Kenta, Hao Wang, Hideki Sudo, and Akihiko Chiba. 2019. “Simple Method to Construct Process Maps for Additive Manufacturing Using a Support Vector Machine.” Additive Manufacturing 27: 353–362.
   Web of Science ®Google Scholar
• Chen, Yingyan, Hongze Wang, Yi Wu, and Haowei Wang. 2020. “Predicting the Printability in Selective Laser Melting with a Supervised Machine Learning Method.” Materials 13 (22): 5063.
   PubMed Web of Science ®Google Scholar
• Csurka, Gabriela, Diane Larlus, Florent Perronnin, and France Meylan. 2013. “What is a Good Evaluation Measure for Semantic Segmentation?.” Paper presented at the Bmvc, 24th British Machine Vision Conference (BMVC), University of Bristol, September 9–13.
   Google Scholar
• Drissi-Daoudi, Rita, Vigneashwara Pandiyan, Roland Logé, Sergey Shevchik, Giulio Masinelli, Hossein Ghasemi-Tabasi, Annapaola Parrilli, and Kilian Wasmer. 2022. “Differentiation of Materials and Laser Powder Bed Fusion Processing Regimes from Airborne Acoustic Emission Combined with Machine Learning.” Virtual and Physical Prototyping 17 (2): 181–204.
   Web of Science ®Google Scholar
• Everton, Sarah K, Matthias Hirsch, Petros Stravroulakis, Richard K Leach, and Adam T Clare. 2016. “Review of in-Situ Process Monitoring and in-Situ Metrology for Metal Additive Manufacturing.” Materials & Design 95: 431–445.
   Web of Science ®Google Scholar
• Goh, Guo Dong, Swee Leong Sing, and Wai Yee Yeong. 2021. “A Review on Machine Learning in 3D Printing: Applications, Potential, and Challenges.” Artificial Intelligence Review 54 (1): 63–94.
   Web of Science ®Google Scholar
• Grasso, Marco, Vittorio Laguzza, Quirico Semeraro, and Bianca Maria Colosimo. 2017. “In-Process Monitoring of Selective Laser Melting: Spatial Detection of Defects via Image Data Analysis.” Journal of Manufacturing Science and Engineering 139 (5): 051001.
   Web of Science ®Google Scholar
• Hochreiter, Sepp, and Jürgen Schmidhuber. 1997. “Long Short-Term Memory.” Neural Computation 9 (8): 1735–1780.
   PubMed Web of Science ®Google Scholar
• Huang, De Jun, and Hua Li. 2021. “A Machine Learning Guided Investigation of Quality Repeatability in Metal Laser Powder Bed Fusion Additive Manufacturing.” Materials & Design 203: 109606.
   Web of Science ®Google Scholar
• Joshi, Sunil C, and Abdullah A Sheikh. 2015. “3D Printing in Aerospace and its Long-Term Sustainability.” Virtual and Physical Prototyping 10 (4): 175–185.
   Web of Science ®Google Scholar
• Khanzadeh, Mojtaba, Sudipta Chowdhury, Mohammad Marufuzzaman, Mark A Tschopp, and Linkan Bian. 2018. “Porosity Prediction: Supervised-Learning of Thermal History for Direct Laser Deposition.” Journal of Manufacturing Systems 47: 69–82.
   Web of Science ®Google Scholar
• Khanzadeh, Mojtaba, Sudipta Chowdhury, Mark A Tschopp, Haley R Doude, Mohammad Marufuzzaman, and Linkan Bian. 2019. “In-Situ Monitoring of Melt Pool Images for Porosity Prediction in Directed Energy Deposition Processes.” IISE Transactions 51 (5): 437–455.
   Web of Science ®Google Scholar
• King, Wayne E, Andrew T Anderson, Robert M Ferencz, Neil E Hodge, Chandrika Kamath, Saad A Khairallah, and Alexander M Rubenchik. 2015. “Laser Powder Bed Fusion Additive Manufacturing of Metals; Physics, Computational, and Materials Challenges.” Applied Physics Reviews 2 (4): 041304.
   Web of Science ®Google Scholar
• Kouprianoff, D., N. Luwes, E. Newby, I. Yadroitsava, and I. Yadroitsev. 2017. “On-Line Monitoring of Laser Powder Bed Fusion by Acoustic Emission: Acoustic Emission for Inspection of Single Tracks Under Different Powder Layer Thickness.” Paper presented at the 2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech).
   Google Scholar
• Ladani, Leila, and Maryam Sadeghilaridjani. 2021. “Review of Powder Bed Fusion Additive Manufacturing for Metals.” Metals 11 (9): 1391.
   Web of Science ®Google Scholar
• Lane, Brandon, Shawn Moylan, Eric P Whitenton, and Li Ma. 2016. “Thermographic Measurements of the Commercial Laser Powder Bed Fusion Process at NIST.” Rapid Prototyping Journal 22 (5): 778–787.
   PubMed Web of Science ®Google Scholar
• Leung, Chu Lun Alex, Sebastian Marussi, Robert C. Atwood, Michael Towrie, Philip J. Withers, and Peter D. Lee. 2018. “In Situ X-ray Imaging of Defect and Molten Pool Dynamics in Laser Additive Manufacturing.” Nature Communications 9 (1): 1–9.
   PubMed Web of Science ®Google Scholar
• Liu, Sen, Aaron P Stebner, Branden B Kappes, and Xiaoli Zhang. 2021. “Machine Learning for Knowledge Transfer Across Multiple Metals Additive Manufacturing Printers.” Additive Manufacturing 39: 101877.
   Web of Science ®Google Scholar
• Lu, Q. Y., N. V. Nguyen, A. J. W. Hum, T. Tran, and C. H. Wong. 2019. “Optical in-Situ Monitoring and Correlation of Density and Mechanical Properties of Stainless Steel Parts Produced by Selective Laser Melting Process Based on Varied Energy Density.” Journal of Materials Processing Technology 271: 520–531.
   Web of Science ®Google Scholar
• Lu, Q. Y., N. V. Nguyen, A. J. W. Hum, T. Tran, and C. H. Wong. 2020. “Identification and Evaluation of Defects in Selective Laser Melted 316L Stainless Steel Parts via in-Situ Monitoring and Micro Computed Tomography.” Additive Manufacturing 35: 101287.
   Web of Science ®Google Scholar
• McCann, Ronan, Muhannad A Obeidi, Cian Hughes, Éanna McCarthy, Darragh S Egan, Rajani K Vijayaraghavan, Ajey M Joshi, Victor Acinas Garzon, Denis P Dowling, and Patrick J McNally. 2021. “In-Situ Sensing, Process Monitoring and Machine Control in Laser Powder Bed Fusion: A Review.” Additive Manufacturing 45: 102058.
   Web of Science ®Google Scholar
• Okaro, Ikenna A, Sarini Jayasinghe, Chris Sutcliffe, Kate Black, Paolo Paoletti, and Peter L Green. 2019. “Automatic Fault Detection for Laser Powder-bed Fusion Using Semi-Supervised Machine Learning.” Additive Manufacturing 27: 42–53.
   Web of Science ®Google Scholar
• Oliveira, João Pedro, A. D. LaLonde, and J. Ma. 2020. “Processing Parameters in Laser Powder Bed Fusion Metal Additive Manufacturing.” Materials & Design 193: 108762.
   Web of Science ®Google Scholar
• Pandiyan, Vigneashwara, Rita Drissi-Daoudi, Sergey Shevchik, Giulio Masinelli, Tri Le-Quang, Roland Logé, and Kilian Wasmer. 2021. “Semi-supervised Monitoring of Laser Powder Bed Fusion Process Based on Acoustic Emissions.” Virtual and Physical Prototyping 16 (4): 481–497.
   Web of Science ®Google Scholar
• Raplee, J., A. Plotkowski, Michael M Kirka, R. Dinwiddie, A. Okello, Ryan R Dehoff, and Sudarsanam Suresh Babu. 2017. “Thermographic Microstructure Monitoring in Electron Beam Additive Manufacturing.” Scientific Reports 7 (1): 1–16.
   PubMed Web of Science ®Google Scholar
• Scime, Luke, and Jack Beuth. 2018a. “Anomaly Detection and Classification in a Laser Powder Bed Additive Manufacturing Process Using a Trained Computer Vision Algorithm.” Additive Manufacturing 19: 114–126.
   Web of Science ®Google Scholar
• Scime, Luke, and Jack Beuth. 2018b. “A Multi-Scale Convolutional Neural Network for Autonomous Anomaly Detection and Classification in a Laser Powder Bed Fusion Additive Manufacturing Process.” Additive Manufacturing 24: 273–286.
   Web of Science ®Google Scholar
• Shevchik, Sergey A, Christoph Kenel, Christian Leinenbach, and Kilian Wasmer. 2018. “Acoustic Emission for in Situ Quality Monitoring in Additive Manufacturing Using Spectral Convolutional Neural Networks.” Additive Manufacturing 21: 598–604.
   Web of Science ®Google Scholar
• Sing, S. L., C. N. Kuo, C. T. Shih, C. C. Ho, and C. K. Chua. 2021. “Perspectives of Using Machine Learning in Laser Powder Bed Fusion for Metal Additive Manufacturing.” Virtual and Physical Prototyping 16 (3): 372–386.
   Web of Science ®Google Scholar
• Song, Lijun, Wenkang Huang, Xu Han, and Jyoti Mazumder. 2016. “Real-time Composition Monitoring Using Support Vector Regression of Laser-induced Plasma for Laser Additive Manufacturing.” IEEE Transactions on Industrial Electronics 64 (1): 633–642.
   Web of Science ®Google Scholar
• Tianhua, Chen, Zheng Siqun, and Yu Junchuan. 2018. “Remote Sensing Image Segmentation Using Improved DeepLab Network.” Measurement and Control Technology 37 (11): 40–45.
   Google Scholar
• Tofail, Syed AM, Elias P Koumoulos, Amit Bandyopadhyay, Susmita Bose, Lisa O’Donoghue, and Costas Charitidis. 2018. “Additive Manufacturing: Scientific and Technological Challenges, Market Uptake and Opportunities.” Materials Today 21 (1): 22–37.
   Web of Science ®Google Scholar
• Wang, Di, Linqing Liu, Guowei Deng, Cheng Deng, Yuchao Bai, Yongqiang Yang, Weihui Wu, Jie Chen, Yang Liu, and Yonggang Wang. 2022. “Recent Progress on Additive Manufacturing of Multi-Material Structures with Laser Powder bed Fusion.” Virtual and Physical Prototyping 17 (2): 329–365.
   Web of Science ®Google Scholar
• Wang, Jingdong, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu, Mingkui Tan, and Xinggang Wang. 2020. “Deep High-Resolution Representation Learning for Visual Recognition.” IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (10): 3349–3364.
   Web of Science ®Google Scholar
• Wang, Chengcheng, X. P. Tan, S. B. Tor, and C. S. Lim. 2020. “Machine Learning in Additive Manufacturing: State-of-the-Art and Perspectives.” Additive Manufacturing 36: 101538.
   Web of Science ®Google Scholar
• Ye, Dongsen, Geok Soon Hong, Yingjie Zhang, Kunpeng Zhu, and Jerry Ying Hsi Fuh. 2018. “Defect Detection in Selective Laser Melting Technology by Acoustic Signals with Deep Belief Networks.” The International Journal of Advanced Manufacturing Technology 96 (5): 2791–2801.
   Web of Science ®Google Scholar
• Zhang, Rongyu, Lixuan Du, Qi Xiao, and Jiaming Liu. 2020. “Comparison of Backbones for Semantic Segmentation Network.” Paper presented at the Journal of Physics: Conference Series, Suzhou, China, March 20–22.
   Google Scholar
• Zhang, Bin, Shunyu Liu, and Yung C Shin. 2019. “In-process Monitoring of Porosity During Laser Additive Manufacturing Process.” Additive Manufacturing 28: 497–505.
   Web of Science ®Google Scholar
• zur Jacobsmühlen, Joschka, Stefan Kleszczynski, Gerd Witt, and Dorit Merhof. 2015. “Elevated Region Area Measurement for Quantitative Analysis of Laser Beam Melting Process Stability.” Paper presented at the 26th International Solid Freeform Fabrication Symposium, Austin, TX.
   Google Scholar
• zur Jacobsmühlen, Joschka, Stefan Kleszczynski, Gerd Witt, and Dorit Merhof. 2017. “Compound Quality Assessment in Laser Beam Melting Processes Using Layer Images.” Paper presented at the 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Torino, Italy, May 22–25.
   Google Scholar