{"id":"https://openalex.org/W4414433219","doi":"https://doi.org/10.1109/case58245.2025.11164003","title":"Kolmogorov-Arnold Networks (KAN)-enabled Incremental Learning for Online Process Monitoring of Additive Manufacturing","display_name":"Kolmogorov-Arnold Networks (KAN)-enabled Incremental Learning for Online Process Monitoring of Additive Manufacturing","publication_year":2025,"publication_date":"2025-08-17","ids":{"openalex":"https://openalex.org/W4414433219","doi":"https://doi.org/10.1109/case58245.2025.11164003"},"language":"en","primary_location":{"id":"doi:10.1109/case58245.2025.11164003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case58245.2025.11164003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},"type":"article","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/A5051066860","display_name":"Boris Oskolkov","orcid":null},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boris Oskolkov","raw_affiliation_strings":["School of Industrial Engineering and Management at Oklahoma State University,Stillwater,OK,USA,74078"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management at Oklahoma State University,Stillwater,OK,USA,74078","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093030165","display_name":"Emmanuel Yangue","orcid":null},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emmanuel Yangue","raw_affiliation_strings":["School of Industrial Engineering and Management at Oklahoma State University,Stillwater,OK,USA,74078"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management at Oklahoma State University,Stillwater,OK,USA,74078","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026893647","display_name":"Wenmeng Tian","orcid":"https://orcid.org/0000-0002-3462-0692"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenmeng Tian","raw_affiliation_strings":["Mississippi State University,Department of Industrial and Systems Engineering,Mississippi State, MS,USA,39762"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mississippi State University,Department of Industrial and Systems Engineering,Mississippi State, MS,USA,39762","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636632","display_name":"Chen Kan","orcid":"https://orcid.org/0000-0003-1885-0516"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Kan","raw_affiliation_strings":["The University of Texas at Arlington,Department of Industrial, Manufacturing, and Systems Engineering,Arlington,TX,USA,76019"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Arlington,Department of Industrial, Manufacturing, and Systems Engineering,Arlington,TX,USA,76019","institution_ids":["https://openalex.org/I189196454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003491617","display_name":"Chenang Liu","orcid":"https://orcid.org/0000-0002-6571-0682"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenang Liu","raw_affiliation_strings":["School of Industrial Engineering and Management at Oklahoma State University,Stillwater,OK,USA,74078"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management at Oklahoma State University,Stillwater,OK,USA,74078","institution_ids":["https://openalex.org/I115475287"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.22766579,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1396","last_page":"1402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.9409000277519226,"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"}},"topics":[{"id":"https://openalex.org/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.9409000277519226,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.6710000038146973},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6409000158309937},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5164999961853027},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.47029998898506165},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.46369999647140503},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42820000648498535},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.4036000072956085},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.3562000095844269}],"concepts":[{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.6710000038146973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6430000066757202},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6409000158309937},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5164999961853027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5095999836921692},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.47029998898506165},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.46369999647140503},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42820000648498535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4242999851703644},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.4036000072956085},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.3393000066280365},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.3138999938964844},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27889999747276306},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case58245.2025.11164003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case58245.2025.11164003","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"explores":[2],"the":[3,18,33,41,56,79,95,101,145,148,159,163],"advances":[4],"of":[5,50,126,147,162],"Kolmogorov-Arnold":[6],"Networks":[7],"(KANs)":[8],"with":[9,22,55,75],"potential":[10],"applications":[11],"in":[12,90,112,122,156],"additive":[13],"manufacturing":[14],"(AM),":[15],"such":[16,86],"as":[17,87],"online":[19],"process":[20,109],"monitoring":[21],"competitive":[23],"cost":[24],"efficiency.":[25],"With":[26],"unique":[27],"architecture":[28],"and":[29,97,107,114,131],"flexible":[30,98],"activation":[31,99],"functions,":[32,100],"emerging":[34],"KANs":[35],"provide":[36],"a":[37,152],"promising":[38,160],"alternative":[39],"to":[40,58,77,137],"multi-layer":[42],"perception":[43],"(MLP)-based":[44],"models,":[45],"enabling":[46],"better":[47],"modeling":[48],"capability":[49],"complex":[51,80],"AM":[52,81,139],"processes,":[53],"especially":[54],"need":[57],"involve":[59],"incremental":[60,92,133,166],"learning.":[61,93],"The":[62,118,141],"proposed":[63,149,164],"knowledge":[64],"distillation":[65],"(KD)":[66],"empowered":[67],"CNN-KAN":[68],"framework":[69,102],"integrates":[70],"convolutional":[71],"neural":[72],"network":[73],"(CNN)":[74],"KAN":[76],"model":[78],"processes":[82],"while":[83],"addressing":[84],"challenges":[85],"catastrophic":[88],"forgetting":[89],"domain":[91],"Utilizing":[94],"KD":[96],"enables":[103],"accurate":[104],"anomaly":[105],"detection":[106],"real-time":[108],"monitoring,":[110],"even":[111],"dynamic":[113,138],"evolving":[115],"data":[116],"environments.":[117],"framework\u2019s":[119],"novelty":[120],"lies":[121],"its":[123],"first-time":[124],"integration":[125],"KANs,":[127],"CNN-based":[128],"feature":[129],"extraction,":[130],"KD-based":[132],"learning":[134,167],"specifically":[135],"tailored":[136],"processes.":[140],"experimental":[142],"results":[143],"highlight":[144],"effectiveness":[146],"method":[150],"through":[151],"practical":[153],"case":[154],"study":[155],"AM,":[157],"showcasing":[158],"future":[161],"KAN-enabled":[165],"framework.":[168]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
