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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.type
masterThesis
en_US
heal.language
en
en_US
heal.access
free
en_US
heal.license
http://creativecommons.org/licenses/by-nc/4.0
en_US
heal.recordProvider
School of Science and Technology, MSc in Data Science
en_US
heal.publicationDate
2019-12-17
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.advisorName
Kotsakis, Rigas
el
heal.committeeMemberName
Tzetzis, Dimitrios
en
heal.committeeMemberName
Martinopoulos, Georgios
el
heal.academicPublisher
IHU
el
heal.academicPublisherID
ihu
en_US


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