Object identification in smart foundries

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Jalava, Kalle
dc.contributor.author Uyan, Tekin
dc.date.accessioned 2018-09-03T12:41:20Z
dc.date.available 2018-09-03T12:41:20Z
dc.date.issued 2018-08-28
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/33748
dc.description.abstract There are many manual steps need to be taken to materialize a foundry’s final product. The critical data gathered during these steps are mostly recorded manually via papers, which decrease efficiency of data collection the confidentiality of the data, and cause risk of human errors. Accordingly, there is a significant need for an automated data gathering through intelligent objects and visualization of these data in a digital world in order to improve the foundry ecosystem, sustainable metals processing, contribute material and energy saving, and feed customer demands. The goal of this thesis is to investigate the digital object identification techniques that would contribute to Smart Foundry concept. The thesis is part of the FIN3D (Finnish Industry New Age 3D) project by researching the new methods for utilization of additive manufacturing through contribution to integration of Internet of Things (IoT) in smart foundries. The study focuses on finding methods for digital identification of the objects in foundries and producing intelligent castings, meaning carrying a unique identification and retain or store data about itself while being capable of communicating effectively with (IoT) elements. Interviews are held with three Finnish and one Turkish foundries varies in terms of casting techniques and product types. The information gathered from the interviews resulted a wide problem definition which constructed experimental parts of the thesis. The experiments are divided in two main parts. The first part focuses on a novel method of utilization of additive manufacturing for direct part marking(DPM) of the castings with 2D matrix codes (2D barcodes) in the beginning of production phase. The second part is about integration RFID technology through object identification which is divided in two sub parts; the first episode is the implantation the RFID tags in foundry objects such as molds to digitally trace the consumable objects in a foundry ecosystem, while second episode is mainly about theoretical simulation of the radio frequency functionality through a chipless RFID in a metal part which assumed to be an option for automation in foundries through digital casting identifications. 3D printed 2D codes are successfully utilized creating unique identification DPMs in castings. A practical method for object’s identification via RFID tags are developed and tested. A simple two bits of chipless RFID is simulated in the metallic environment and theoretically proved its feasibility. The experimental processes are analyzed and outcomes are evaluated for further improvements. en
dc.format.extent 69+6
dc.language.iso en en
dc.title Object identification in smart foundries en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Kemian tekniikan korkeakoulu fi
dc.subject.keyword industry 4.0 en
dc.subject.keyword smart foundry en
dc.subject.keyword direct part marking en
dc.subject.keyword digitalization en
dc.subject.keyword intelligent castings en
dc.subject.keyword sustainable metals processing en
dc.identifier.urn URN:NBN:fi:aalto-201809034873
dc.programme.major Sustainable Metals Processing fi
dc.programme.mcode CHEM3026 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Orkas, Juhani
dc.programme Master's Programme in Chemical, Biochemical and Materials Engineering fi
dc.location PK fi
local.aalto.electroniconly yes
local.aalto.openaccess no


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