{"id":"https://openalex.org/W4394805312","doi":"https://doi.org/10.1109/tevc.2024.3388725","title":"Feature Extraction With Genetic Programming for Root Cause Identification in Manufacturing With Interpretable Machine Learning","display_name":"Feature Extraction With Genetic Programming for Root Cause Identification in Manufacturing With Interpretable Machine Learning","publication_year":2024,"publication_date":"2024-04-15","ids":{"openalex":"https://openalex.org/W4394805312","doi":"https://doi.org/10.1109/tevc.2024.3388725"},"language":"en","primary_location":{"id":"doi:10.1109/tevc.2024.3388725","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2024.3388725","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-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/A5112034700","display_name":"Chan Gyu Lee","orcid":"https://orcid.org/0000-0002-3618-6711"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chan Gyu Lee","raw_affiliation_strings":["Department of Industrial and Systems Engineering, Dongguk University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, Dongguk University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027137736","display_name":"Sungbum Jun","orcid":"https://orcid.org/0000-0003-0835-552X"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungbum Jun","raw_affiliation_strings":["Department of Industrial and Systems Engineering, Dongguk University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-0835-552X","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, Dongguk University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I205490536"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9155,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76147047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"29","issue":"4","first_page":"1029","last_page":"1040"},"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":0.8948000073432922,"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":0.8948000073432922,"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/T11201","display_name":"Metallurgy and Material Forming","score":0.8813999891281128,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.8400999903678894,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/genetic-programming","display_name":"Genetic programming","score":0.7135867476463318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6342703700065613},{"id":"https://openalex.org/keywords/root","display_name":"Root (linguistics)","score":0.6066725254058838},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6017748117446899},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5881036520004272},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.579033613204956},{"id":"https://openalex.org/keywords/root-cause-analysis","display_name":"Root cause analysis","score":0.5279977321624756},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5008330345153809},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46310776472091675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4628659188747406},{"id":"https://openalex.org/keywords/root-cause","display_name":"Root cause","score":0.43291473388671875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2489686906337738},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.09346112608909607},{"id":"https://openalex.org/keywords/forensic-engineering","display_name":"Forensic engineering","score":0.07357010245323181}],"concepts":[{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.7135867476463318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6342703700065613},{"id":"https://openalex.org/C171078966","wikidata":"https://www.wikidata.org/wiki/Q111029","display_name":"Root (linguistics)","level":2,"score":0.6066725254058838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6017748117446899},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5881036520004272},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.579033613204956},{"id":"https://openalex.org/C130963320","wikidata":"https://www.wikidata.org/wiki/Q1401207","display_name":"Root cause analysis","level":2,"score":0.5279977321624756},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5008330345153809},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46310776472091675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4628659188747406},{"id":"https://openalex.org/C84945661","wikidata":"https://www.wikidata.org/wiki/Q7366567","display_name":"Root cause","level":2,"score":0.43291473388671875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2489686906337738},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.09346112608909607},{"id":"https://openalex.org/C77595967","wikidata":"https://www.wikidata.org/wiki/Q3151013","display_name":"Forensic engineering","level":1,"score":0.07357010245323181},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tevc.2024.3388725","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2024.3388725","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1593481303","https://openalex.org/W1813219539","https://openalex.org/W1970090588","https://openalex.org/W1973890821","https://openalex.org/W2025512130","https://openalex.org/W2026686302","https://openalex.org/W2045250232","https://openalex.org/W2058048553","https://openalex.org/W2093598546","https://openalex.org/W2093865894","https://openalex.org/W2114714326","https://openalex.org/W2132196970","https://openalex.org/W2141007997","https://openalex.org/W2153617975","https://openalex.org/W2295985801","https://openalex.org/W2743579215","https://openalex.org/W2765317657","https://openalex.org/W2927733588","https://openalex.org/W2995140071","https://openalex.org/W2997591727","https://openalex.org/W3002572154","https://openalex.org/W3011975155","https://openalex.org/W3014985883","https://openalex.org/W3039810648","https://openalex.org/W3080746720","https://openalex.org/W3083080580","https://openalex.org/W3090586341","https://openalex.org/W3109180935","https://openalex.org/W3112305567","https://openalex.org/W3131773838","https://openalex.org/W3138819813","https://openalex.org/W3153861455","https://openalex.org/W3166617745","https://openalex.org/W3173360689","https://openalex.org/W3181533277","https://openalex.org/W3199355704","https://openalex.org/W3203496010","https://openalex.org/W4200224444","https://openalex.org/W4220751842","https://openalex.org/W4226032077","https://openalex.org/W4282934797","https://openalex.org/W4285805192","https://openalex.org/W4310748417","https://openalex.org/W4312208408","https://openalex.org/W4312702461","https://openalex.org/W4323929052","https://openalex.org/W4388134641"],"related_works":["https://openalex.org/W2030594396","https://openalex.org/W2535098331","https://openalex.org/W3045668461","https://openalex.org/W2202104725","https://openalex.org/W4255366506","https://openalex.org/W2056250485","https://openalex.org/W4280640835","https://openalex.org/W2885334669","https://openalex.org/W2111856191","https://openalex.org/W4230518569"],"abstract_inverted_index":{"For":[0],"fault":[1],"detection":[2,21],"(FD)":[3],"in":[4,103],"manufacturing,":[5],"various":[6],"machine":[7],"learning":[8],"(ML)":[9],"models":[10,26,150],"have":[11,32],"been":[12,33],"widely":[13],"applied":[14],"to":[15,35,48,61,110,118,126,159],"minimise":[16],"human":[17],"intervention":[18],"and":[19,52,57,133,155],"improve":[20,62],"performance.":[22],"Even":[23],"though":[24],"ML":[25],"such":[27],"as":[28],"neural":[29],"networks":[30],"(NN)":[31],"shown":[34],"identify":[36],"faults":[37],"effectively,":[38],"root":[39],"cause":[40],"identification":[41],"(RCI)":[42],"is":[43],"becoming":[44],"more":[45],"difficult":[46],"due":[47],"their":[49],"black-box":[50,161],"structures":[51],"the":[53,88,121,147,160],"trade-off":[54],"between":[55],"accuracy":[56],"interpretability.":[58],"In":[59,120],"order":[60],"performance":[63,89,157],"while":[64],"maintaining":[65],"interpretability,":[66],"we":[67],"propose":[68],"a":[69],"new":[70],"framework":[71],"named":[72],"FERMAT":[73,145],"(Feature":[74],"Extraction":[75],"for":[76,80,99],"finding":[77],"Root":[78],"causes":[79],"Manufacturing":[81],"Applications":[82],"with":[83,130,136],"Tree-based":[84],"algorithms),":[85],"which":[86],"enhances":[87],"of":[90],"height-limited":[91],"decision":[92,112],"trees":[93,113],"(C4.5)":[94],"through":[95],"dimensionally-aware":[96],"genetic":[97],"programming":[98],"feature":[100],"extraction.":[101],"Especially":[102],"FERMAT,":[104],"only":[105],"interpretable":[106],"features":[107,154],"are":[108],"extracted":[109],"prevent":[111],"from":[114],"delivering":[115],"uninterpretable":[116],"expressions":[117],"practitioners.":[119],"present":[122],"study,":[123],"FERMAT\u2019s":[124],"applicability":[125],"RCI":[127],"was":[128],"verified":[129],"both":[131],"manufacturing":[132],"non-manufacturing":[134],"datasets":[135],"different":[137],"imbalance":[138],"ratios.":[139],"The":[140],"experimental":[141],"results":[142],"showed":[143],"that":[144],"outperformed":[146],"other":[148],"single-tree-based":[149],"by":[151],"extracting":[152],"good":[153],"delivered":[156],"comparable":[158],"models.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
