Thermal Measurements Based on Image Processing for In Situ Monitoring of 3D Fused Filament Fabrication (FFF)

Article Preview

Abstract:

Nowadays new applications based on the 3D printing technique demand increasingly strict product quality requirements. The in-situ monitoring of variables associated with the manufacturing process through the application of different techniques could help to evaluate the process and ultimately to ensure product quality. In this regard, the acquisition and evaluation of variables and indexes derived from thermographic analysis during the process are key for an early defect detection and can contribute to quality estimation. In this work, a new methodology is proposed for the monitoring and analysis of the additive manufacturing process based on the processing of thermographic images from an LWIR (Long Wave Infrared) camera. The methodology and the suitability of the variables and indexes extracted during the monitoring of the manufacturing process are discussed for the case of a 3D fused filament fabrication of polymers.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

81-90

Citation:

Online since:

October 2023

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2023 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] A. Yadollahi and N. Shamsaei, "Additive manufacturing of fatigue resistant materials: Challenges and opportunities," Int J Fatigue, vol. 98, p.14–31, 2017.

DOI: 10.1016/j.ijfatigue.2017.01.001

Google Scholar

[2] K. E. Lee, N. Morad, T. T. Teng, and B. T. Poh, "Development, characterization and the application of hybrid materials in coagulation/flocculation of wastewater: A review," Chemical Engineering Journal, vol. 203, p.370–386, 2012.

DOI: 10.1016/j.cej.2012.06.109

Google Scholar

[3] D. Fico, D. Rizzo, R. Casciaro, and C. E. Corcione, "A Review of Polymer-Based Materials for Fused Filament Fabrication (FFF): Focus on Sustainability and Recycled Materials," Polymers (Basel), vol. 14, no. 3, 2022.

DOI: 10.3390/polym14030465

Google Scholar

[4] J. R. C. Dizon, A. H. Espera, Q. Chen, and R. C. Advincula, "Mechanical characterization of 3D-printed polymers," Addit Manuf, vol. 20, p.44–67, 2018.

DOI: 10.1016/j.addma.2017.12.002

Google Scholar

[5] V. Authors, Aditive Manufacturing: Materials, Processes, Quantifications and Applications, vol. 83, no. 1. The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom: Elsevier Inc. Butterworth-Heinemann, 2018.

DOI: 10.1017/aer.2019.85

Google Scholar

[6] S. A. M. Tofail, E. P. Koumoulos, A. Bandyopadhyay, S. Bose, L. O'Donoghue, and C. Charitidis, "Additive manufacturing: scientific and technological challenges, market uptake and opportunities," Materials Today, vol. 21, no. 1, p.22–37, 2018.

DOI: 10.1016/j.mattod.2017.07.001

Google Scholar

[7] K.S. Prakash, T. Nancharaih, and V.V.S. Rao, "Additive Manufacturing Techniques in Manufacturing -An Overview," Mater Today Proc, vol. 5, no. 2, p.3873–3882, 2018.

DOI: 10.1016/j.matpr.2017.11.642

Google Scholar

[8] A. Paolini, S. Kollmannsberger, and E. Rank, "Additive manufacturing in construction: A review on processes, applications, and digital planning methods," Addit Manuf, vol. 30, no. July, p.100894, 2019.

DOI: 10.1016/j.addma.2019.100894

Google Scholar

[9] M. Srivastava, S. Rathee, V. Patel, A. Kumar, and P. G. Koppad, "A review of various materials for additive manufacturing: Recent trends and processing issues," Journal of Materials Research and Technology, vol. 21, p.2612–2641, 2022.

DOI: 10.1016/j.jmrt.2022.10.015

Google Scholar

[10] N.P. Aleshin, M.v. Grigor'ev, N.A. Shchipakov, M.A. Prilutskii, and V.v. Murashov, "Applying nondestructive testing to quality control of additive manufactured parts," Russian Journal of Nondestructive Testing, vol. 52, no. 10, p.600–609, 2016.

DOI: 10.1134/S1061830916100028

Google Scholar

[11] Y. Fu, A. Downey, L. Yuan, A. Pratt, and Y. Balogun, "In situ monitoring for fused filament fabrication process: A review," Addit Manuf, vol. 38, no. July 2020, p.101749, 2021.

DOI: 10.1016/j.addma.2020.101749

Google Scholar

[12] H. R. Vanaei, M. Shirinbayan, M. Deligant, S. Khelladi, and A. Tcharkhtchi, "In-Process Monitoring of Temperature Evolution during Fused Filament Fabrication: A Journey from Numerical to Experimental Approaches," Thermo, vol. 1, no. 3, p.332–360, 2021.

DOI: 10.3390/thermo1030021

Google Scholar

[13] G. Gaussorges and S. Chomet, Infrared Thermography, vol. 56, no. 11. Springer Netherlands, 1993.

Google Scholar

[14] H. Haußecker and P. Geißler, Handbook of Computer Vision and Applications. Volume 1. Sensors and Imaging, vol. 1. San Diego, California, U.S.A.: Academic Press, 2000.

DOI: 10.1016/B978-0-12-379777-3.X5000-6

Google Scholar

[15] R. Usamentiaga, P. Venegas, J. Guerediaga, L. Vega, J. Molleda, and F. G. Bulnes, "Infrared thermography for temperature measurement and non-destructive testing," Sensors (Switzerland), vol. 14, no. 7, p.12305–12348, 2014.

DOI: 10.3390/s140712305

Google Scholar

[16] K. Murali, D. v. Rama Koti Reddy, and R. Mulaveesala, "Application of image fusion for the IR images in frequency modulated thermal wave imaging for Non Destructive Testing (NDT)," Mater Today Proc, vol. 5, no. 1, p.544–549, 2018.

DOI: 10.1016/j.matpr.2017.11.116

Google Scholar

[17] D. Perpetuini, D. Formenti, D. Cardone, C. Filippini, and A. Merla, "Regions of interest selection and thermal imaging data analysis in sports and exercise science: A narrative review," Physiol Meas, vol. 42, no. 8, 2021.

DOI: 10.1088/1361-6579/ac0fbd

Google Scholar

[18] I. Nardi, E. Lucchi, T. de Rubeis, and D. Ambrosini, "Quantification of heat energy losses through the building envelope: A state-of-the-art analysis with critical and comprehensive review on infrared thermography," Build Environ, vol. 146, no. July, p.190–205, 2018.

DOI: 10.1016/j.buildenv.2018.09.050

Google Scholar

[19] F. Mercuri et al., "Metastructure of illuminations by infrared thermography," J Cult Herit, vol. 31, p.53–62, 2018.

DOI: 10.1016/j.culher.2017.10.008

Google Scholar

[20] P.J. Zarco-Periñán and J.L. Martínez-Ramos, "Influencial factors in thermographic analysis in substations," Infrared Phys Technol, vol. 90, p.207–213, 2018, doi:10.1016/j.infrared. 2018.03.014.

DOI: 10.1016/j.infrared.2018.03.014

Google Scholar

[21] S. Gallardo-saavedra and L. Hern, "Image Resolution Influence in Aerial Thermographic Inspections of Photovoltaic Plants," IEEE Trans Industr Inform, vol. 14, no. 12, p.5678–5686, 2018.

DOI: 10.1109/TII.2018.2865403

Google Scholar

[22] A. Choudhary, T. Mian, and S. Fatima, "Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images," Measurement (Lond), vol. 176, no. February, p.109196, 2021.

DOI: 10.1016/j.measurement.2021.109196

Google Scholar

[23] A. Fernandez, A. Souto, C. Gonzalez, and R. Mendez-Rial, "Embedded vision system for monitoring arc welding with thermal imaging and deep learning," 2020 International Conference on Omni-Layer Intelligent Systems, COINS 2020, 2020.

DOI: 10.1109/COINS49042.2020.9191650

Google Scholar

[24] J. V. C. Vargas et al., "Normalized methodology for medical infrared imaging," Infrared Phys Technol, vol. 52, no. 1, p.42–47, Jan. 2009.

DOI: 10.1016/j.infrared.2008.11.003

Google Scholar

[25] L. Patino et al., "Fusion of Heterogenous Sensor Data in Border Surveillance," Sensors, vol. 22, no. 19, p.1–17, 2022.

DOI: 10.3390/s22197351

Google Scholar

[26] N. H. Quttineh, P. M. Olsson, T. Larsson, and H. Lindell, "An optimization approach to the design of outdoor thermal fire detection systems," Fire Saf J, vol. 129, no. August 2021, 2022.

DOI: 10.1016/j.firesaf.2022.103548

Google Scholar

[27] "ASTM D638-14. Standard Test Method for Tensile Properties of Plastics." ASTM International, West Conshohocken, PA, 2014, 2014.

Google Scholar

[28] M. A. Savelonas, C. N. Veinidis, and T. K. Bartsokas, "Computer Vision and Pattern Recognition for the Analysis of 2D/3D Remote Sensing Data in Geoscience: A Survey," Remote Sens (Basel), vol. 14, no. 23, 2022.

DOI: 10.3390/rs14236017

Google Scholar

[29] B. Jahne, H. Haußecker, and P. Geißler, Handbook of Computer Vision and Applications. Volume 2. Signal Processing and Pattern Recognition., vol. 2. San Diego, California, U.S.A.: Academic Press, 1999.

DOI: 10.1007/s00138-006-0021-7

Google Scholar

[30] J. Ma, X. Jiang, A. Fan, J. Jiang, and J. Yan, "Image Matching from Handcrafted to Deep Features: A Survey," Int J Comput Vis, vol. 129, no. 1, p.23–79, 2021.

DOI: 10.1007/s11263-020-01359-2

Google Scholar

[31] M. Zhai, X. Xiang, N. Lv, and X. Kong, "Optical flow and scene flow estimation: A survey," Pattern Recognit, vol. 114, p.107861, 2021.

DOI: 10.1016/j.patcog.2021.107861

Google Scholar

[32] S. T. H. Shah and X. Xuezhi, "Traditional and modern strategies for optical flow: an investigation," SN Appl Sci, vol. 3, no. 3, p.1–14, 2021.

DOI: 10.1007/s42452-021-04227-x

Google Scholar

[33] R. Badarinath and V. Prabhu, "Real-Time Sensing of Output Polymer Flow Temperature and Volumetric Flowrate in Fused Filament Fabrication Process," Materials, vol. 15, no. 2, 2022.

DOI: 10.3390/ma15020618

Google Scholar