{"id":"https://openalex.org/W7161178500","doi":"https://doi.org/10.1016/j.array.2026.100888","title":"A critical survey of machine learning - powered vision inspection in semiconductors manufacturing","display_name":"A critical survey of machine learning - powered vision inspection in semiconductors manufacturing","publication_year":2026,"publication_date":"2026-05-14","ids":{"openalex":"https://openalex.org/W7161178500","doi":"https://doi.org/10.1016/j.array.2026.100888"},"language":"en","primary_location":{"id":"doi:10.1016/j.array.2026.100888","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2026.100888","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.array.2026.100888","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5118972720","display_name":"Yamral Kassanew Akele","orcid":null},"institutions":[{"id":"https://openalex.org/I39815113","display_name":"Georgia Southern University","ror":"https://ror.org/04agmb972","country_code":"US","type":"education","lineage":["https://openalex.org/I39815113"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yamral Kassanew Akele","raw_affiliation_strings":["Georgia Southern University, Robotics Process Development Laboratory (RPDL), Statesboro, GA, 30458, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Southern University, Robotics Process Development Laboratory (RPDL), Statesboro, GA, 30458, USA","institution_ids":["https://openalex.org/I39815113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020408010","display_name":"Vladimir Gurau","orcid":"https://orcid.org/0000-0003-2742-9061"},"institutions":[{"id":"https://openalex.org/I39815113","display_name":"Georgia Southern University","ror":"https://ror.org/04agmb972","country_code":"US","type":"education","lineage":["https://openalex.org/I39815113"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vladimir Gurau","raw_affiliation_strings":["Georgia Southern University, Robotics Process Development Laboratory (RPDL), Statesboro, GA, 30458, USA"],"raw_orcid":"https://orcid.org/0000-0003-2742-9061","affiliations":[{"raw_affiliation_string":"Georgia Southern University, Robotics Process Development Laboratory (RPDL), Statesboro, GA, 30458, USA","institution_ids":["https://openalex.org/I39815113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020408010"],"corresponding_institution_ids":["https://openalex.org/I39815113"],"apc_list":{"value":1350,"currency":"USD","value_usd":1350},"apc_paid":{"value":1350,"currency":"USD","value_usd":1350},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68544601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"100888","last_page":"100888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.44029998779296875,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.44029998779296875,"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":0.045099999755620956,"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"}},{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.035100001841783524,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/machine-vision","display_name":"Machine vision","score":0.43050000071525574},{"id":"https://openalex.org/keywords/semiconductor-device-fabrication","display_name":"Semiconductor device fabrication","score":0.4090999960899353},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.27239999175071716},{"id":"https://openalex.org/keywords/manufacturing","display_name":"Manufacturing","score":0.26440000534057617}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47110000252723694},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4634999930858612},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C66018809","wikidata":"https://www.wikidata.org/wiki/Q1570432","display_name":"Semiconductor device fabrication","level":3,"score":0.4090999960899353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4034999907016754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35100001096725464},{"id":"https://openalex.org/C117671659","wikidata":"https://www.wikidata.org/wiki/Q11049265","display_name":"Manufacturing engineering","level":1,"score":0.3409999907016754},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.32019999623298645},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27639999985694885},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C175700187","wikidata":"https://www.wikidata.org/wiki/Q187939","display_name":"Manufacturing","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.26409998536109924}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.array.2026.100888","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2026.100888","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.array.2026.100888","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2026.100888","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2092243497","https://openalex.org/W2509669877","https://openalex.org/W2798589477","https://openalex.org/W2919932305","https://openalex.org/W2951293392","https://openalex.org/W2997583607","https://openalex.org/W3020045356","https://openalex.org/W3039229032","https://openalex.org/W3047291564","https://openalex.org/W3171640879","https://openalex.org/W4207016755","https://openalex.org/W4381460233","https://openalex.org/W4387789872","https://openalex.org/W4391823537","https://openalex.org/W4412497077","https://openalex.org/W4413282965"],"related_works":[],"abstract_inverted_index":{"We":[0,24,62,98],"provide":[1],"a":[2,197],"critical":[3],"investigation":[4],"of":[5,15,52,66,68,95,140,170,199,207,214],"the":[6,13,64,69,80,87,96,100,127,180,184,208,227,238],"current":[7],"achievements,":[8],"challenges":[9,102],"and":[10,50,59,74,92,120,131,168,243],"limitations":[11,81],"in":[12,21,72,82,86,183,221,245],"field":[14],"machine":[16],"learning":[17],"(ML)-assisted":[18],"vision":[19,38,105,216],"inspection":[20,106,125,200,217],"semiconductors":[22,53],"manufacturing.":[23],"analyze":[25],"ML":[26],"architectures":[27],"such":[28,153],"as":[29,77,154],"convolutional":[30],"neural":[31],"networks,":[32],"hybrid":[33],"frameworks":[34],"combining":[35],"classical":[36],"computer":[37],"with":[39,137,150],"deep":[40],"learning,":[41],"ensemble":[42],"techniques,":[43],"or":[44,85,234],"transformer-based":[45],"approaches":[46],"for":[47,161,191,240],"automatic":[48],"detection":[49,159],"classification":[51,132],"defects":[54],"at":[55,232],"various":[56,146],"manufacturing":[57,203,224,248],"stages":[58],"defect":[60,129],"types.":[61],"assess":[63],"strength":[65],"evidence":[67],"reported":[70,128,151],"accuracies":[71,133],"detecting":[73],"classifying":[75],"defects,":[76,163],"reflected":[78],"by":[79],"models\u2019":[83],"validation":[84],"size,":[88],"diversity,":[89],"class":[90],"imbalance":[91],"labeling":[93,166],"inconsistencies":[94],"datasets.":[97],"discuss":[99],"scalability":[101,242],"faced":[103],"when":[104],"models":[107],"are":[108,219,230],"transitioning":[109],"from":[110],"prototype":[111,233],"to":[112,165,173,189],"high-volume":[113,222],"manufacturing,":[114],"present":[115],"research":[116],"gaps,":[117],"ethical":[118],"considerations":[119],"future":[121],"directions.":[122],"In":[123],"some":[124,192],"tasks,":[126],"detections":[130],"often":[134],"reach":[135],"98\u201399%":[136],"increased":[138],"performance":[139,171],"4.6\u20138.6-fold":[141],"over":[142,176],"baseline":[143],"methods.":[144],"Nevertheless,":[145],"technical":[147],"difficulties":[148],"remain":[149],"implementations":[152],"high":[155],"false-positive":[156],"rates,":[157],"reduced":[158],"accuracy":[160,201],"nanoscale":[162],"sensitivity":[164],"inconsistencies,":[167],"degradation":[169],"due":[172],"data":[174],"drift":[175],"production":[177],"batches.":[178],"Also,":[179],"processing":[181],"time":[182],"range":[185],"between":[186],"millisecond-level":[187],"inference":[188],"seconds":[190],"specific":[193],"segmentation":[194],"tasks":[195],"represents":[196],"trade-off":[198],"against":[202],"throughput.":[204],"An":[205],"assessment":[206],"deployment":[209],"maturity":[210],"shows":[211],"only":[212],"17%":[213],"ML-assisted":[215],"systems":[218],"deployed":[220],"semiconductor":[223,247],"environments,":[225],"whilst":[226],"remaining":[228],"83%":[229],"applied":[231],"pilot":[235],"scale,":[236],"highlighting":[237],"need":[239],"improved":[241],"robustness":[244],"industrial":[246],"applications.":[249]},"counts_by_year":[],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2026-05-15T00:00:00"}