Multimedia Data Analysis in 3D Printing Technology
| dc.contributor.author | Tzimtzimis, Emmanouil | en |
| dc.date.accessioned | 2020-05-20T14:10:04Z | |
| dc.date.available | 2020-05-21T00:00:48Z | |
| dc.date.issued | 2020-05-20 | |
| dc.identifier.uri | https://repository.ihu.edu.gr//xmlui/handle/11544/29449 | |
| dc.rights | Default License | |
| dc.subject | 3D printing | en |
| dc.subject | Multimedia | el |
| dc.subject | Data Analysis | el |
| dc.subject | Machine learning | el |
| dc.title | Multimedia Data Analysis in 3D Printing Technology | en |
| heal.abstract | This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. Nowadays, the necessity of collecting data from several sources has become a mandatory field not only for the businesses growth but also for research and experimentation purposes. Moreover, the 3D printing technology is a unique additive manufacturing process that tends to change the market limits and thus, the supply chain and logistics of businesses. This dissertation is an intensive research on how the manipulation of multimedia data can affect one of the most common 3D printing technologies, the Fused Deposition Modeling (FDM). With the use of state-of-the-art equipment of the International Hellenic University, such as FDM 3D printer, and various specialized software, different scenarios were studied in order to classify whether a 3D printing process is successful or not, regarding the different designing, and printing parameters, with the addition of some image related functions. | el |
| heal.academicPublisher | IHU | el |
| heal.academicPublisherID | ihu | en_US |
| heal.access | free | en_US |
| heal.advisorName | Kotsakis, Rigas | el |
| heal.committeeMemberName | Tzetzis, Dimitrios | en |
| heal.committeeMemberName | Martinopoulos, Georgios | el |
| heal.language | en | en_US |
| heal.license | http://creativecommons.org/licenses/by-nc/4.0 | en_US |
| heal.publicationDate | 2019-12-17 | |
| heal.recordProvider | School of Science and Technology, MSc in Data Science | en_US |
| heal.type | masterThesis | en_US |
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