{"id":"https://openalex.org/W7214992567","doi":"https://doi.org/10.21872/annual2025_8813","title":"Image-Based Quality Control for Additive Manufacturing through Layer-by-Layer Analysis","display_name":"Image-Based Quality Control for Additive Manufacturing through Layer-by-Layer Analysis","publication_year":2026,"publication_date":"2026-09-30","ids":{"openalex":"https://openalex.org/W7214992567","doi":"https://doi.org/10.21872/annual2025_8813"},"language":"en","primary_location":{"id":"doi:10.21872/annual2025_8813","doi":"https://doi.org/10.21872/annual2025_8813","is_oa":false,"landing_page_url":"https://doi.org/10.21872/annual2025_8813","pdf_url":null,"source":{"id":"https://openalex.org/S7407087832","display_name":"IISE Annual Conference & Expo","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IISE Annual Conference & Expo 2025","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5153584285","display_name":"Jesus Diaz","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jesus Diaz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080164801","display_name":"Chaitanya Mahajan","orcid":"https://orcid.org/0000-0002-9490-2181","observed_orcids":["https://orcid.org/0000-0002-9490-2181","https://orcid.org/0000-0002-2321-981X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaitanya Mahajan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153580383","display_name":"Unaffiliated","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Unaffiliated","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153662252","display_name":"Casey Tran","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Casey Tran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153616971","display_name":"Satyajayant Misra","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Satyajayant Misra","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5153555894","display_name":"Srikanthan Ramesh","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srikanthan Ramesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7704462,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.9063000082969666,"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"}},"topics":[{"id":"https://openalex.org/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.9063000082969666,"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"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.07429999858140945,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.009399999864399433,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/additive-manufacturing-quality-control","display_name":"additive manufacturing quality control","score":0.9559999704360962},{"id":"https://openalex.org/keywords/image-based-quality-inspection","display_name":"image-based quality inspection","score":0.5860000252723694},{"id":"https://openalex.org/keywords/layer-by-layer-analysis","display_name":"layer-wise analysis","score":0.7960000038146973},{"id":"https://openalex.org/keywords/spatial-transformer-network","display_name":"spatial transformer network","score":0.7940000295639038},{"id":"https://openalex.org/keywords/siamese-network","display_name":"Siamese network","score":0.9639999866485596},{"id":"https://openalex.org/keywords/one-shot-learning","display_name":"one-shot learning","score":0.9079999923706055},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"image segmentation","score":0.6240000128746033},{"id":"https://openalex.org/keywords/dimensional-accuracy","display_name":"dimensional accuracy","score":0.49000000953674316},{"id":"https://openalex.org/keywords/in-situ-monitoring","display_name":"in situ monitoring","score":0.5720000267028809}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6722000241279602},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.614300012588501},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5891000032424927},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5742999911308289},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5329999923706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5203999876976013},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.4496999979019165},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44110000133514404},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.43619999289512634},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3894999921321869},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3391999900341034},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C2780841897","wikidata":"https://www.wikidata.org/wiki/Q25349015","display_name":"Digital manufacturing","level":2,"score":0.32339999079704285},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3165000081062317},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.303600013256073},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27390000224113464},{"id":"https://openalex.org/C51704429","wikidata":"https://www.wikidata.org/wiki/Q827792","display_name":"Quality control","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C2987875673","wikidata":"https://www.wikidata.org/wiki/Q187939","display_name":"Manufacturing process","level":2,"score":0.26660001277923584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21872/annual2025_8813","doi":"https://doi.org/10.21872/annual2025_8813","is_oa":false,"landing_page_url":"https://doi.org/10.21872/annual2025_8813","pdf_url":null,"source":{"id":"https://openalex.org/S7407087832","display_name":"IISE Annual Conference & Expo","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IISE Annual Conference & Expo 2025","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.651199996471405,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7214900706","https://openalex.org/W4409581514","https://openalex.org/W4404061221","https://openalex.org/W2989656882","https://openalex.org/W3010932738","https://openalex.org/W4214524140","https://openalex.org/W3177730877","https://openalex.org/W4394975341","https://openalex.org/W2966005396","https://openalex.org/W4319944925"],"abstract_inverted_index":{"Quality":[0],"control":[1,149,172],"for":[2,49,55,72,150],"additive":[3,151,177],"manufacturing":[4],"is":[5,129],"investigated":[6],"by":[7],"leveraging":[8],"deep":[9],"learning-based":[10],"segmentation":[11,60],"techniques":[12],"using":[13],"neural":[14,64],"networks.":[15],"The":[16,62,101],"majority":[17],"of":[18,91,109],"existing":[19,78],"studies":[20],"adopt":[21],"methodologies":[22],"from":[23],"Convolutional":[24],"Neural":[25],"Networks":[26,48],"(CNNs)":[27],"that":[28,138],"apply":[29],"uniform":[30],"spatial":[31,50],"scopes":[32],"across":[33],"the":[34,88,106,161],"whole":[35],"image.":[36],"In":[37],"this":[38],"study,":[39],"we":[40],"propose":[41],"a":[42,118,166],"novel":[43],"approach":[44],"incorporating":[45],"Spatial":[46],"Transformer":[47],"alignment":[51],"and":[52,94,97,173],"Siamese":[53],"networks":[54],"one-shot":[56],"learning":[57],"investigations":[58],"on":[59,87],"accuracy.":[61],"state-of-the-art":[63],"net":[65],"architecture":[66],"employed":[67],"will":[68,104],"feature":[69],"in-network":[70],"scaling":[71],"enhanced":[73],"performance.":[74],"Identifying":[75],"gaps":[76],"in":[77,117,147,176],"methodologies,":[79],"our":[80],"method":[81],"addresses":[82],"unexplored":[83],"avenues,":[84],"specifically":[85],"focusing":[86],"in-site":[89],"quantification":[90],"measuring":[92],"over":[93],"under":[95],"extrusion":[96,127],"layer-wise":[98],"structural":[99],"integrity.":[100],"envisioned":[102],"experiments":[103],"compare":[105],"material":[107,136],"properties":[108,137],"printed":[110],"parts":[111],"to":[112,126,131,141],"their":[113],"nominal":[114],"digital":[115],"representations":[116],"layer-by-layer":[119],"fashion.":[120],"This":[121],"methodology,":[122],"with":[123],"its":[124],"application":[125],"processes,":[128],"poised":[130],"offer":[132],"valuable":[133],"insights":[134],"into":[135],"are":[139],"challenging":[140],"discern":[142],"conventionally,":[143],"thus":[144],"driving":[145],"advancements":[146],"quality":[148,159,171],"manufacturing.":[152,178],"By":[153],"providing":[154],"precise":[155],"geometric":[156],"or":[157],"dimensional":[158],"control,":[160],"proposed":[162],"monitoring":[163],"system":[164],"represents":[165],"significant":[167],"step":[168],"toward":[169],"ensuring":[170],"process":[174],"efficiency":[175]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-01T00:00:00"}