Augmented Reality in Foundry Manufacture

dc.contributor.authorEugster, Sandro
dc.contributor.mentorInglese, Terry
dc.contributor.mentorKorkut, Safak
dc.date.accessioned2024-12-03T19:06:38Z
dc.date.available2024-12-03T19:06:38Z
dc.date.issued2022
dc.description.abstractThis thesis investigates how the technology of Augmented Reality (AR) can influence a red brass foundry and its complex process. On the one hand, it is investigated in detail how the influence on the availability of the machine is and whether, if necessary, the disturbances and waiting times can be reduced by using visualizations with AR. On the other hand, it will be investigated whether the quality factor of the machine can be increased by visualizing process data from the foundry process. The advantages and limitations of the technology were explored in a first step, the process complexity was elicited. The digital age has also arrived in the production of companies in recent years. In order for European and especially Swiss companies to still be able to produce their products in their own country, it is important to eliminate waste and make manufacturing processes as effective as possible. This allows higher margins to be placed on products and bypasses the need to outsource production to countries such as China. Wherever possible, repetitive tasks performed by humans are automated by robots. Not for every application a complete replacement of humans by robots makes sense, because the human factor must not be neglected.
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/48653
dc.language.isoen
dc.publisherHochschule für Wirtschaft FHNW
dc.spatialOlten
dc.subject.ddc330 - Wirtschaft
dc.titleAugmented Reality in Foundry Manufacture
dc.type11 - Studentische Arbeit
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.StudentsWorkTypeMaster
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutMaster of Science
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relation.isMentorOfPublication79281801-c965-4a1c-afa5-3e9195745028
relation.isMentorOfPublication.latestForDiscovery9d4b2213-faa9-4797-8268-793afc77ec8f
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