Development of a manufacturability predictor for periodic cellular structures in a selective laser melting process via experiment and ANN modelling

References

• Chuang, C.-H., S. Chen, R.-J. Yang, and P. Vogiatzis. 2018. “Topology Optimization with Additive Manufacturing Consideration for Vehicle Load Path Development.” International Journal for Numerical Methods in Engineering 113 (8): 1434–1445.
   Web of Science ®Google Scholar
• Coatanéa, E., H. P. N. Nagarajan, S. Panicker, R. Prod’hon, H. Mokhtarian, A. Chakraborti, H. Paris, I. F. Ituarte, and K. R. Haapala. 2020. “Systematic Manufacturability Evaluation Using Dimensionless Metrics and Singular Value Decomposition: A Case Study for Additive Manufacturing.” The International Journal of Advanced Manufacturing Technology 115 (3): 715–731.
   Web of Science ®Google Scholar
• Ding, L., S. Tan, W. Chen, Y. Jin, and Y. Zhang. 2021. “Manufacturability Analysis of Extremely Fine Porous Structures for Selective Laser Melting Process of Ti6Al4V Alloy.” Rapid Prototyping Journal 27 (8): 1523–1537.
   Web of Science ®Google Scholar
• du Plessis, A., C. Broeckhoven, I. Yadroitsava, I. Yadroitsev, C. H. Hands, R. Kunju, and D. Bhate. 2019. “Beautiful and Functional: A Review of Biomimetic Design in Additive Manufacturing.” Additive Manufacturing 27: 408–427.
   Web of Science ®Google Scholar
• Goh, G. D., N. M. B. Hamzah, and W. Y. Yeong. 2022. Anomaly Detection in Fused Filament Fabrication Using Machine Learning, 3D Printing and Additive Manufacturing.
   Google Scholar
• Goh, G. D., S. L. Sing, and W. Y. Yeong. 2020. “A Review on Machine Learning in 3D Printing: Applications, Potential, and Challenges.” Artificial Intelligence Review 54 (1): 63–94.
   Web of Science ®Google Scholar
• Gupta, S. K., W. C. Regli, D. Das, and D. S. Nau. 1997. “Automated Manufacturability Analysis: A Survey.” Reasearch in Engineering Design 9: 168–190.
   Web of Science ®Google Scholar
• Hammel, E. C., O. L. R. Ighodaro, and O. I. Okoli. 2014. “Processing and Properties of Advanced Porous Ceramics: An Application Based Review.” Ceramics International 40 (10): 15351–15370.
   Web of Science ®Google Scholar
• https://nl.mathworks.com/help/deeplearning/ref/trainscg.html?searchHighlight = trainscg&s_tid = srchtitle.
   Google Scholar
• Janik, H., and M. Marzec. 2015. “A Review: Fabrication of Porous Polyurethane Scaffolds.” Materials Science & Engineering. C, Materials for Biological Applications 48: 586–591.
   PubMed Web of Science ®Google Scholar
• Ko, H., P. Witherell, Y. Lu, S. Kim, and D. W. Rosen. 2021. “Machine Learning and Knowledge Graph Based Design Rule Construction for Additive Manufacturing.” Additive Manufacturing 37: 101620.
   Web of Science ®Google Scholar
• Koklu, M., I. Cinar, and Y. S. Taspinar. 2021. “Classification of Rice Varieties with Deep Learning Methods.” Computers and Electronics in Agriculture 187: 106285.
   PubMed Web of Science ®Google Scholar
• Kotadia, H. R., G. Gibbons, A. Das, and P. D. Howes. 2021. “A Review of Laser Powder Bed Fusion Additive Manufacturing of Aluminium Alloys: Microstructure and Properties.” Additive Manufacturing 46: 102155.
   Web of Science ®Google Scholar
• Laguna, O. H., P. F. Lietor, F. J. I. Godino, and F. A. Corpas-Iglesias. 2021. “A Review on Additive Manufacturing and Materials for Catalytic Applications: Milestones, key Concepts, Advances and Perspectives.” Materials & Design 208: 109927.
   Web of Science ®Google Scholar
• Lebaal, N., Y. Zhang, F. Demoly, S. Roth, S. Gomes, and A. Bernard. 2019. “Optimised Lattice Structure Configuration for Additive Manufacturing.” CIRP Annals 68 (1): 117–120.
   Web of Science ®Google Scholar
• Menon, A., B. Póczos, A. W. Feinberg, and N. R. Washburn. 2019. “Optimization of Silicone 3D Printing with Hierarchical Machine Learning.” 3D Printing and Additive Manufacturing 6 (4): 181–189.
   Google Scholar
• Nazir, A., K. M. Abate, A. Kumar, and J.-Y. Jeng. 2019. “A State-of-the-art Review on Types, Design, Optimization, and Additive Manufacturing of Cellular Structures.” The International Journal of Advanced Manufacturing Technology 104 (9-12): 3489–3510.
   Web of Science ®Google Scholar
• Oh, Y., H. Ko, T. Sprock, W. Z. Bernstein, and S. Kwon. 2021. “Part Decomposition and Evaluation Based on Standard Design Guidelines for Additive Manufacturability and Assemblability.” Additive Manufacturing 37: 101702.
   Web of Science ®Google Scholar
• Oh, Y., C. Zhou, and S. Behdad. 2018. “Part Decomposition and Assembly-Based (Re) Design for Additive Manufacturing: A Review.” Additive Manufacturing 22: 230–242.
   Web of Science ®Google Scholar
• Pham, M. S., C. Liu, I. Todd, and J. Lertthanasarn. 2019. “Damage-tolerant Architected Materials Inspired by Crystal Microstructure.” Nature 565 (7739): 305–311.
   PubMed Web of Science ®Google Scholar
• Rudolph, J.-P., and C. Emmelmann. 2017. “Analysis of Design Guidelines for Automated Order Acceptance in Additive Manufacturing.” Procedia CIRP 60: 187–192.
   Google Scholar
• Sames, W. J., F. A. List, S. Pannala, R. R. Dehoff, and S. S. Babu. 2016. “The Metallurgy and Processing Science of Metal Additive Manufacturing.” International Materials Reviews 61 (5): 315–360.
   Web of Science ®Google Scholar
• Schoeck, G. 1956 Dislocation Theory of Plasticity of Metals.” Advances in Applied Mechanics Volume 41956: 229–279.
   Google Scholar
• D. Shamvedi, O.J. McCarthy, E. O’Donoghue, C. Danilenkoff, P. O’Leary, R. Raghavendra, 3D Metal Printed Heat Sinks with Longitudinally Varying Lattice Structure Sizes Using Direct Metal Laser Sintering, Virtual and Physical Prototyping 13(4) (2018) 301-310.
   Web of Science ®Google Scholar
• Shi, Y., Y. Zhang, S. Baek, W. De Backer, and R. Harik. 2018. “Manufacturability Analysis for Additive Manufacturing Using a Novel Feature Recognition Technique.” Computer-Aided Design and Applications 15 (6): 941–952.
   Google Scholar
• Tan, S., X. Zhang, L. Ding, and Y. Zhang. 2021. An Efficient Layer Construction Method to Generate Accurate Printing Toolpaths of Periodic Cellular Structures for Selective Laser Melting Process Solid Freeform Fabrication 2021: Proceedings of the 32th Annual International Solid Freeform Fabrication Symposium, 2021.
   Google Scholar
• Tedia, S., and C. B. Williams. 2016. Manufacturability analysis tool for Additive manufatcuring using voxel-based geometric modeling, Solid Freeform Fabrication 2016: Proceedings of the 27th Annual International Solid Freeform Fabrication Symposium.
   Google Scholar
• Thomas, D. 2009. “The Development of Design Rules for Selective Laser Melting.” PhD Thesis, University of Wales, Cardiff.
   Google Scholar
• Thompson, M. K., G. Moroni, T. Vaneker, G. Fadel, R. I. Campbell, I. Gibson, A. Bernard, et al. 2016. “Design for Additive Manufacturing: Trends, Opportunities, Considerations, and Constraints.” CIRP Annals 65 (2): 737–760.
   Web of Science ®Google Scholar
• Van Bael, S., G. Kerckhofs, M. Moesen, G. Pyka, J. Schrooten, and J. P. Kruth. 2011. “Micro-CT-based Improvement of Geometrical and Mechanical Controllability of Selective Laser Melted Ti6Al4V Porous Structures.” Materials Science and Engineering: A 528 (24): 7423–7431.
   Web of Science ®Google Scholar
• Vaneker, T., A. Bernard, G. Moroni, I. Gibson, and Y. Zhang. 2020. “Design for Additive Manufacturing: Framework and Methodology.” CIRP Annals 69 (2): 578–599.
   Web of Science ®Google Scholar
• Wang, C., 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
• White, B. C., A. Garland, R. Alberdi, and B. L. Boyce. 2021. “Interpenetrating Lattices with Enhanced Mechanical Functionality.” Additive Manufacturing 38: 101741.
   Web of Science ®Google Scholar
• Yadroitsev, I., I. Yadroitsava, P. Bertrand, and I. Smurov. 2012. “Factor Analysis of Selective Laser Melting Process Parameters and Geometrical Characteristics of Synthesized Single Tracks.” Rapid Prototyping Journal 18 (3): 201–208.
   Web of Science ®Google Scholar
• Yan, C., L. Hao, A. Hussein, S. L. Bubb, P. Young, and D. Raymont. 2014. “Evaluation of Light-Weight AlSi10Mg Periodic Cellular Lattice Structures Fabricated via Direct Metal Laser Sintering.” Journal of Materials Processing Technology 214 (4): 856–864.
   Web of Science ®Google Scholar
• Yao, X., S. K. Moon, and G. Bi. 2017. “A Hybrid Machine Learning Approach for Additive Manufacturing Design Feature Recommendation.” Rapid Prototyping Journal 23 (6): 983–997.
   Web of Science ®Google Scholar
• Zhang, J., G. Lu, and Z. You. 2020a. “Large Deformation and Energy Absorption of Additively Manufactured Auxetic Materials and Structures: A Review.” Composites Part B: Engineering 201: 108340.
   Web of Science ®Google Scholar
• Zhang, Y., S. Tan, L. Ding, and A. Bernard. 2021. “A Toolpath-Based Layer Construction Method for Designing & Printing Porous Structure.” CIRP Annals 70 (1): 123–126.
   Web of Science ®Google Scholar
• Zhang, Y., Z. Wang, Y. Zhang, S. Gomes, and A. Bernard. 2020b. “Bio-inspired Generative Design for Support Structure Generation and Optimization in Additive Manufacturing (AM).” CIRP Annals 69 (1): 117–120.
   Web of Science ®Google Scholar
• Zhang, Y., S. Yang, and Y. F. Zhao. 2020. “Manufacturability Analysis of Metal Laser-Based Powder bed Fusion Additive Manufacturing—a Survey.” The International Journal of Advanced Manufacturing Technology 110 (1-2): 57–78.
   Web of Science ®Google Scholar
• Zhang, Y., and Y. F. Zhao. 2022. “Hybrid Sparse Convolutional Neural Networks for Predicting Manufacturability of Visual Defects of Laser Powder bed Fusion Processes.” Journal of Manufacturing Systems 62: 835–845.
   Web of Science ®Google Scholar