DC FieldValueLanguage
dc.contributor.authorLewke, Marcel-
dc.contributor.authorNielsen, Sören-
dc.contributor.authorList, Alexander-
dc.contributor.authorGärtner, Frank-
dc.contributor.authorKlassen, Thomas-
dc.contributor.authorFay, Alexander-
dc.date.accessioned2022-04-07T08:35:22Z-
dc.date.available2022-04-07T08:35:22Z-
dc.date.issued2021-09-
dc.description.abstractIn recent years, cold spraying (CS) has emerged as a promising technology for repair applications, particularly for oxidation-sensitive materials. In order to obtain an optimum repair result that fulfills the highest requirements regarding material properties, simple geometric shape restoration is not sufficient. Any additive manufacturing process results in particular features in microstructure, possible defects and respective – potentially even anisotropic – mechanical properties. To systematically tailor these microstructures and properties to the specific component and geometry requires complex routines. This work proposes the design of a knowledge-based cold spray repair system that facilitates a complete individual repair procedure for aircraft components. This system includes the elements of (i) reverse engineering to analyze, classify and generate digital data of the damaged component, (ii) pre-processing to obtain the ideal conditions for the CS process, (iii) toolpath planning to optimize robotics for the CS process, (iv) on-line monitoring to ensure process quality, (v) post-processing and (vi) performance testing of the material properties to meet the challenging requirements of the aerospace industry. By using an industrial robot and computer-aided planning of the trajectories, components are to be repaired under cold spray and geometrical conditions for ideal material deposition. The goal is to obtain repaired components that fulfill the required property profile equally well as respective new parts.de_DE
dc.description.sponsorshipAutomatisierungstechnikde_DE
dc.description.sponsorshipDTEC.bwde_DE
dc.description.sponsorshipWerkstoffkundede_DE
dc.language.isoengde_DE
dc.relationComputergesteuerte Bauteilaufarbeitungde_DE
dc.subjectCold Gas Sprayingde_DE
dc.subjectRobotikde_DE
dc.subjectdtec.bwde_DE
dc.titleKnowledge-based Optimization of Cold Spray for Aircraft Component Repairde_DE
dc.typeConference Objectde_DE
dc.relation.conference26th International Conference on Emerging Technologies and Factory Automation (ETFA) 2021de_DE
local.submission.typeonly-metadatade_DE
dc.description.peerReviewedYesde_DE
dc.type.conferenceObjectConference Paperde_DE
item.fulltext_sNo Fulltext-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeConference Object-
crisitem.author.deptAutomatisierungstechnik-
crisitem.author.deptWerkstoffkunde-
crisitem.author.deptWerkstoffkunde-
crisitem.author.deptWerkstoffkunde-
crisitem.author.deptAutomatisierungstechnik-
crisitem.author.orcid0000-0002-9521-3273-
crisitem.author.orcid0000-0002-1922-654X-
crisitem.author.parentorgFakultät für Maschinenbau und Bauingenieurwesen-
crisitem.author.parentorgFakultät für Maschinenbau und Bauingenieurwesen-
crisitem.author.parentorgFakultät für Maschinenbau und Bauingenieurwesen-
crisitem.author.parentorgFakultät für Maschinenbau und Bauingenieurwesen-
crisitem.author.parentorgFakultät für Maschinenbau und Bauingenieurwesen-
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