Parts design and process optimization

Book chapter

Hassanin, Hany, Bidare, Prveen, Zweiri, Yahya and Essa, Khamis 2021. Parts design and process optimization. in: Salunkhe, S., Hussein, H. and Davim, J. (ed.) Applications of Artificial Intelligence in Additive Manufacturing USA IGI Global. pp. 25-49
AuthorsHassanin, Hany, Bidare, Prveen, Zweiri, Yahya and Essa, Khamis
EditorsSalunkhe, S., Hussein, H. and Davim, J.
AbstractArtificial intelligence and additive manufacturing are primary drivers of Industry 4.0, which is reshaping the manufacturing industry. Based on the progressive layer-by-layer principle, additive manufacturing allows for the manufacturing of mechanical parts with a high degree of complexity. In this chapter, a deep learning neural network (DLNN) is introduced to rationalize the effect of cellular structure design factors as well as process variables on physical and mechanical properties utilizing laser powder bed fusion. The models developed were validated and utilized to create process maps. For both design and process optimization, the trained deep learning neural network model showed the highest accuracy. Deep learning neural networks were found to be an effective technique for predicting material properties from limited data sets, as per the findings.
KeywordsDeep learning; Additive manufacturing; Porosity; Powder bed fusion
Page range25-49
Year2021
Book titleApplications of Artificial Intelligence in Additive Manufacturing
PublisherIGI Global
Output statusPublished
Place of publicationUSA
ISBN9781799885160
ISSN2327-0411
2327-042X
Publication dates
PrintDec 2021
Publication process dates
AcceptedNov 2021
Deposited13 Dec 2021
Digital Object Identifier (DOI)https://doi.org/10.4018/978-1-7998-8516-0.ch002
Official URLhttps://www.igi-global.com/chapter/parts-design-and-process-optimization/294047
Related URLhttps://www.igi-global.com/book/applications-artificial-intelligence-additive-manufacturing/271276
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Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
Fan , W., Chen, Y., Li, J., Sun, Y., Feng, F., Hassanin, H. and Sareh, P. 2021. Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications. Structures. 33, pp. 3954-3963. https://doi.org/10.1016/j.istruc.2021.06.110
Porosity, cracks, and mechanical properties of additively manufactured tooling alloys: A review
Bidare, P., Jiménez, A., Hassanin, H. and Essa, K. 2021. Porosity, cracks, and mechanical properties of additively manufactured tooling alloys: A review. Advances in Manufacturing. https://doi.org/10.1007/s40436-021-00365-y
Laser powder bed fusion of Ti-6Al-2Sn-4Zr-6Mo alloy and properties prediction using deep learning approaches
Hassanin, H., Zweiri, Y., Finet, L., Essa, K., Qiu, C. and Attallah, M. 2021. Laser powder bed fusion of Ti-6Al-2Sn-4Zr-6Mo alloy and properties prediction using deep learning approaches. Materials. 14 (8), p. 2056. https://doi.org/10.3390/ma14082056
3DP printing of oral solid formulations: a systematic review
Brambilla, C., Okafor-Muo, O., Hassanin, H. and ElShaer, A. 2021. 3DP printing of oral solid formulations: a systematic review. Pharmaceutics. 13 (3), p. 358. https://doi.org/10.3390/pharmaceutics13030358
Powder-based laser hybrid additive manufacturing of metals: A review
Jimenez, A., Bidare, P., Hassanin, H., Tarlochan, F., Dimov, S. and Essa, K. 2021. Powder-based laser hybrid additive manufacturing of metals: A review. The International Journal of Advanced Manufacturing Technology. 114, pp. 63-96. https://doi.org/10.1007/s00170-021-06855-4
Micro-fabrication of ceramics: additive manufacturing and conventional technologies
Hassanin, H., Essa, K., Elshaer, A., Imbaby, M. and El-Sayed, T. E. 2021. Micro-fabrication of ceramics: additive manufacturing and conventional technologies. Journal of Advanced Ceramics. 10, pp. 1-27. https://doi.org/10.1007/s40145-020-0422-5
4D Printing of origami structures for minimally invasive surgeries using functional scaffold
Langford, T, Mohammed, A., Essa, K., Elshaer, A. and Hassanin, H. 2020. 4D Printing of origami structures for minimally invasive surgeries using functional scaffold. Applied Sciences. 11 (1), p. 332. https://doi.org/10.3390/app11010332
Reconfigurable multipoint forming using waffle-type elastic cushion and variable loading profile
Hassanin, H., Mohammed, M., Abdel-Wahab, A. and Essa, K 2020. Reconfigurable multipoint forming using waffle-type elastic cushion and variable loading profile. Materials.
3D printing of solid oral dosage forms: numerous challenges with unique opportunities
Hassanin, H. 2020. 3D printing of solid oral dosage forms: numerous challenges with unique opportunities. Journal of Pharmaceutical Sciences. https://doi.org/10.1016/j.xphs.2020.08.029
Design optimisation of additively manufactured titanium lattice structures for biomedical implants
El-Sayed, M.A., Essa, K., Ghazy, M. and Hassanin, H. 2020. Design optimisation of additively manufactured titanium lattice structures for biomedical implants. The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-020-05982-8
4D Printing of NiTi auxetic structure with improved ballistic performance
Hassanin, H., Abena, A., Elsayed, M.A. and Essa, K. 2020. 4D Printing of NiTi auxetic structure with improved ballistic performance. Micromachines. 11 (8), p. 745. https://doi.org/doi.org/10.3390/mi11080745