{"id":"https://openalex.org/W4414376499","doi":"https://doi.org/10.1007/978-3-032-05073-1_1","title":"AI-Driven Data Management Framework for Quality Assurance in Additive Manufacturing: A Case Study on the TRUMPF TruPrint 1000","display_name":"AI-Driven Data Management Framework for Quality Assurance in Additive Manufacturing: A Case Study on the TRUMPF TruPrint 1000","publication_year":2025,"publication_date":"2025-09-20","ids":{"openalex":"https://openalex.org/W4414376499","doi":"https://doi.org/10.1007/978-3-032-05073-1_1"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-032-05073-1_1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-05073-1_1","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/978-3-032-05073-1_1","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119338973","display_name":"Faiza Waheed","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142109","display_name":"Rosenheim Technical University of Applied Sciences","ror":"https://ror.org/03hbmgt12","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210142109"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Faiza Waheed","raw_affiliation_strings":["Technische Hochschule Rosenheim, Rosenheim, Germany"],"raw_orcid":"https://orcid.org/0009-0001-2680-1143","affiliations":[{"raw_affiliation_string":"Technische Hochschule Rosenheim, Rosenheim, Germany","institution_ids":["https://openalex.org/I4210142109"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012004953","display_name":"Kai H\u00f6fig","orcid":"https://orcid.org/0000-0001-9613-4801"},"institutions":[{"id":"https://openalex.org/I4210142109","display_name":"Rosenheim Technical University of Applied Sciences","ror":"https://ror.org/03hbmgt12","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210142109"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kai H\u00f6fig","raw_affiliation_strings":["Technische Hochschule Rosenheim, Rosenheim, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9613-4801","affiliations":[{"raw_affiliation_string":"Technische Hochschule Rosenheim, Rosenheim, Germany","institution_ids":["https://openalex.org/I4210142109"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5119685599","display_name":"Fabian Ri\u00df","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142109","display_name":"Rosenheim Technical University of Applied Sciences","ror":"https://ror.org/03hbmgt12","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210142109"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Ri\u00df","raw_affiliation_strings":["Technische Hochschule Rosenheim, Rosenheim, Germany"],"raw_orcid":"https://orcid.org/0009-0003-2609-6856","affiliations":[{"raw_affiliation_string":"Technische Hochschule Rosenheim, Rosenheim, Germany","institution_ids":["https://openalex.org/I4210142109"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5119338973"],"corresponding_institution_ids":["https://openalex.org/I4210142109"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31918803,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quality-assurance","display_name":"Quality assurance","score":0.6884999871253967},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5983999967575073},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5945000052452087},{"id":"https://openalex.org/keywords/documentation","display_name":"Documentation","score":0.5368000268936157},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.48179998993873596},{"id":"https://openalex.org/keywords/visual-inspection","display_name":"Visual inspection","score":0.4659999907016754},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4235999882221222},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.41819998621940613},{"id":"https://openalex.org/keywords/process-control","display_name":"Process control","score":0.38659998774528503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8260999917984009},{"id":"https://openalex.org/C106436119","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assurance","level":3,"score":0.6884999871253967},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5983999967575073},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5945000052452087},{"id":"https://openalex.org/C56666940","wikidata":"https://www.wikidata.org/wiki/Q788790","display_name":"Documentation","level":2,"score":0.5368000268936157},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.48179998993873596},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.4659999907016754},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4235999882221222},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.38659998774528503},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3626999855041504},{"id":"https://openalex.org/C71405471","wikidata":"https://www.wikidata.org/wiki/Q757012","display_name":"Quality management","level":3,"score":0.3621000051498413},{"id":"https://openalex.org/C130963320","wikidata":"https://www.wikidata.org/wiki/Q1401207","display_name":"Root cause analysis","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3546999990940094},{"id":"https://openalex.org/C113644684","wikidata":"https://www.wikidata.org/wiki/Q1356717","display_name":"Statistical process control","level":3,"score":0.329800009727478},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31130000948905945},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.30230000615119934},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C1668388","wikidata":"https://www.wikidata.org/wiki/Q1149776","display_name":"Data management","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2881999909877777},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.2685000002384186},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.25699999928474426},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C198783460","wikidata":"https://www.wikidata.org/wiki/Q629173","display_name":"Management system","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-032-05073-1_1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-05073-1_1","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-032-05073-1_1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-05073-1_1","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2418453408","https://openalex.org/W2611819392","https://openalex.org/W2898724192","https://openalex.org/W2955759746","https://openalex.org/W3006730468","https://openalex.org/W4292819775","https://openalex.org/W4295788896","https://openalex.org/W4368377142","https://openalex.org/W4390174556","https://openalex.org/W4391332950"],"related_works":[],"abstract_inverted_index":{"Our":[0,127],"work":[1],"demonstrates":[2],"an":[3,192],"innovative":[4],"AI-driven":[5,198],"approach":[6,199],"to":[7,30,66,95,101,190,221],"Quality":[8],"Assurance":[9],"(QA)":[10],"in":[11,22,36,104,241],"metal":[12,24],"additive":[13],"manufacturing":[14,148],"(AM).":[15],"We":[16,48,155,212],"focus":[17],"on":[18,251],"real-time":[19],"defect":[20,54],"detection":[21,55,88],"3D":[23,255],"printing,":[25],"which":[26],"is":[27,175],"increasingly":[28],"used":[29,103,176],"manufacture":[31],"small":[32],"parts":[33,40],"for":[34,41,179,186,216,229,236,249],"applications":[35,240],"safety-critical":[37,105,230],"devices,":[38],"including":[39],"the":[42,68,120,125,131,138,144,147,158,201,217],"aerospace,":[43],"automotive,":[44],"and":[45,53,61,77,89,97,118,122,143,165,189,232],"medical":[46],"industries.":[47],"propose":[49,213],"a":[50,73,214],"model-based":[51,238],"failure":[52],"system":[56],"that":[57],"combines":[58],"visual":[59],"monitoring":[60,80],"input":[62],"from":[63],"various":[64],"sensors":[65],"control":[67],"AM":[69,242],"process.":[70],"By":[71],"using":[72],"deep":[74],"learning":[75,194],"model":[76],"incorporating":[78],"live":[79],"of":[81,124,133,140,146,203,219],"data":[82,163],"points,":[83],"we":[84],"enable":[85],"early":[86],"anomaly":[87],"thus":[90],"ensure":[91],"immediate":[92],"operator":[93],"intervention":[94],"stop":[96],"prevent":[98,110],"defective":[99],"prints":[100],"be":[102,247],"applications.":[106],"These":[107],"techniques":[108],"help":[109],"energy":[111],"waste,":[112],"conserve":[113],"material":[114],"costs,":[115],"resources,":[116],"time,":[117],"increase":[119],"safety":[121],"reliability":[123,139],"system.":[126],"prototype":[128],"framework":[129,215,245],"automates":[130],"classification":[132],"multiple":[134,170],"defects,":[135],"improving":[136],"both":[137],"printed":[141],"components":[142],"efficiency":[145],"process":[149,187,223],"by":[150],"suggesting":[151],"in-situ":[152],"improvement":[153],"techniques.":[154],"also":[156,182],"highlight":[157],"technical":[159],"challenges":[160],"associated":[161],"with":[162],"synchronisation":[164],"acquisition,":[166],"as":[167,169,183],"well":[168],"sensor":[171],"integration.":[172],"Data":[173],"collection":[174],"not":[177],"only":[178],"QA":[180,239,250],"but":[181],"valuable":[184],"documentation":[185],"validation":[188],"maintaining":[191],"in-house":[193],"center.":[195],"Overall,":[196],"our":[197],"improves":[200],"accuracy":[202],"non-destructive":[204],"testing":[205],"(NDT)":[206],"over":[207],"traditional":[208],"post-production":[209],"inspection":[210],"methods.":[211],"integration":[218],"AI":[220],"improve":[222],"control,":[224],"making":[225],"it":[226],"more":[227],"reliable":[228],"industries":[231],"providing":[233],"strong":[234],"guidance":[235],"future":[237],"processes.":[243],"This":[244],"can":[246],"applied":[248],"TRUMPF":[252],"TruPrint":[253],"L-PBF":[254],"printing":[256],"machines.":[257]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
