Improving the dimensional accuracy of micro parts 3D printed with projection-based continuous vat photopolymerization using a model-based grayscale optimization method

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buir.contributor.authorGuven, Ege
buir.contributor.authorKarpat, Yigit
buir.contributor.authorCakmakci, Melih
buir.contributor.orcidGuven, Ege|0000-0003-3546-027X
buir.contributor.orcidKarpat, Yigit|0000-0002-3535-8120
buir.contributor.orcidCakmakci, Melih|0000-0002-3535-8120
dc.citation.epage14en_US
dc.citation.spage1en_US
dc.citation.volumeNumber57en_US
dc.contributor.authorGuven, Ege
dc.contributor.authorKarpat, Yigit
dc.contributor.authorCakmakci, Melih
dc.date.accessioned2023-02-14T08:38:58Z
dc.date.available2023-02-14T08:38:58Z
dc.date.issued2022-09
dc.departmentDepartment of Mechanical Engineeringen_US
dc.description.abstractMicro-scale additive manufacturing has seen significant growth over the past years, where improving the accuracy of complex micro-scale geometries is seen as an important challenge. Using grayscale images rather than black and white images during production is an effective method to improve the fabrication quality. This paper presents a model-based optimization method for improving the dimensional accuracy of parts using voxel-based grayscale dynamic optimization during continuous 3D printing. A detailed solidification model has been developed and used to estimate the curing dynamics of the resin used in 3D printing. The irradiance of the light beam projected for each pixel influences a larger volume on the resin than the targeted voxel. The proposed model-based method optimizes the images considering the light distribution from all closely related pixels to maintain the accuracy of the micro part. The results of this method have been applied to the printing of a complex 3D part to show that optimized grayscale images improve the areas with overcuring significantly. It is shown that the number of overcured voxels was reduced by 24.7% compared to the original images. Actual printing results from our experimental setup confirm the improvements in the accuracy and precision of the printing method.en_US
dc.description.provenanceSubmitted by Bilge Kat (bilgekat@bilkent.edu.tr) on 2023-02-14T08:38:58Z No. of bitstreams: 1 Improving_the_dimensional_accuracy_of_micro_parts_3D_printed_with_projection-based_continuous_vat_photopolymerization_using_a_model-based_grayscale_optimization_method.pdf: 3723502 bytes, checksum: 585b083df56d306e9b4489c3992285b8 (MD5)en
dc.description.provenanceMade available in DSpace on 2023-02-14T08:38:58Z (GMT). No. of bitstreams: 1 Improving_the_dimensional_accuracy_of_micro_parts_3D_printed_with_projection-based_continuous_vat_photopolymerization_using_a_model-based_grayscale_optimization_method.pdf: 3723502 bytes, checksum: 585b083df56d306e9b4489c3992285b8 (MD5) Previous issue date: 2022-09en
dc.identifier.doi10.1016/j.addma.2022.102954en_US
dc.identifier.eissn2214-7810
dc.identifier.issn2214-8604
dc.identifier.urihttp://hdl.handle.net/11693/111239
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttps://doi.org/10.1016/j.addma.2022.102954en_US
dc.source.titleAdditive Manufacturingen_US
dc.subjectProcess planningen_US
dc.subjectVat photopolymerizationen_US
dc.subjectModelingen_US
dc.subjectDynamic optimizationen_US
dc.titleImproving the dimensional accuracy of micro parts 3D printed with projection-based continuous vat photopolymerization using a model-based grayscale optimization methoden_US
dc.typeArticleen_US

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