{"id":"https://openalex.org/W3210357862","doi":"https://doi.org/10.1109/dsaa53316.2021.9564228","title":"Explainable anomaly detection for Hot-rolling industrial process","display_name":"Explainable anomaly detection for Hot-rolling industrial process","publication_year":2021,"publication_date":"2021-10-06","ids":{"openalex":"https://openalex.org/W3210357862","doi":"https://doi.org/10.1109/dsaa53316.2021.9564228","mag":"3210357862"},"language":"en","primary_location":{"id":"doi:10.1109/dsaa53316.2021.9564228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa53316.2021.9564228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ruj.uj.edu.pl/xmlui/handle/item/288811","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042993180","display_name":"Jakub Jakubowski","orcid":"https://orcid.org/0000-0002-4773-9086"},"institutions":[{"id":"https://openalex.org/I4210093773","display_name":"ArcelorMittal (Poland)","ror":"https://ror.org/00ppxc472","country_code":"PL","type":"company","lineage":["https://openalex.org/I4210093773","https://openalex.org/I50754188"]},{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Jakub Jakubowski","raw_affiliation_strings":["Arcelor Mittal Poland and AGH University of Science and Technology, Krak\u00f3w, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arcelor Mittal Poland and AGH University of Science and Technology, Krak\u00f3w, Poland","institution_ids":["https://openalex.org/I686019","https://openalex.org/I4210093773"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025773569","display_name":"Przemys\u0142aw Stanisz","orcid":null},"institutions":[{"id":"https://openalex.org/I4210093773","display_name":"ArcelorMittal (Poland)","ror":"https://ror.org/00ppxc472","country_code":"PL","type":"company","lineage":["https://openalex.org/I4210093773","https://openalex.org/I50754188"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Przemyslaw Stanisz","raw_affiliation_strings":["Arcelor Mittal Poland, Krak\u00f3w, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arcelor Mittal Poland, Krak\u00f3w, Poland","institution_ids":["https://openalex.org/I4210093773"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009252880","display_name":"Szymon Bobek","orcid":"https://orcid.org/0000-0002-6350-8405"},"institutions":[{"id":"https://openalex.org/I126596746","display_name":"Jagiellonian University","ror":"https://ror.org/03bqmcz70","country_code":"PL","type":"education","lineage":["https://openalex.org/I126596746"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Szymon Bobek","raw_affiliation_strings":["Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI) and Institute of Applied Computer Science Jagiellonian University, Krak\u00f3w, Poland"],"raw_orcid":"https://orcid.org/0000-0002-6350-8405","affiliations":[{"raw_affiliation_string":"Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI) and Institute of Applied Computer Science Jagiellonian University, Krak\u00f3w, Poland","institution_ids":["https://openalex.org/I126596746"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023890658","display_name":"Grzegorz J. Nalepa","orcid":"https://orcid.org/0000-0002-8182-4225"},"institutions":[{"id":"https://openalex.org/I126596746","display_name":"Jagiellonian University","ror":"https://ror.org/03bqmcz70","country_code":"PL","type":"education","lineage":["https://openalex.org/I126596746"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Grzegorz J. Nalepa","raw_affiliation_strings":["Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI) and Institute of Applied Computer Science Jagiellonian University, Krak\u00f3w, Poland"],"raw_orcid":"https://orcid.org/0000-0002-8182-4225","affiliations":[{"raw_affiliation_string":"Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI) and Institute of Applied Computer Science Jagiellonian University, Krak\u00f3w, Poland","institution_ids":["https://openalex.org/I126596746"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042993180"],"corresponding_institution_ids":["https://openalex.org/I4210093773","https://openalex.org/I686019"],"apc_list":null,"apc_paid":null,"fwci":2.7997,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.9213634,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9814000129699707,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9811000227928162,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/autoencoder","display_name":"Autoencoder","score":0.807959794998169},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7909832000732422},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6733825206756592},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6668568253517151},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.6535489559173584},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6231361627578735},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6222934722900391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5336264967918396},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.51490318775177},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.44139528274536133},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4315774142742157},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38873767852783203},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34427809715270996},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2047283947467804},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1551329493522644},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.13989561796188354}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.807959794998169},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7909832000732422},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6733825206756592},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6668568253517151},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.6535489559173584},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6231361627578735},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6222934722900391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5336264967918396},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.51490318775177},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.44139528274536133},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4315774142742157},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38873767852783203},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34427809715270996},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2047283947467804},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1551329493522644},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.13989561796188354},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/dsaa53316.2021.9564228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa53316.2021.9564228","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},{"id":"pmh:oai:ruj.uj.edu.pl:item/288811","is_oa":true,"landing_page_url":"https://ruj.uj.edu.pl/xmlui/handle/item/288811","pdf_url":null,"source":{"id":"https://openalex.org/S4306400316","display_name":"Homo Politicus (Academy of Humanities and Economics in Lodz)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"publikacja pokonferencyjna"}],"best_oa_location":{"id":"pmh:oai:ruj.uj.edu.pl:item/288811","is_oa":true,"landing_page_url":"https://ruj.uj.edu.pl/xmlui/handle/item/288811","pdf_url":null,"source":{"id":"https://openalex.org/S4306400316","display_name":"Homo Politicus (Academy of Humanities and Economics in Lodz)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"publikacja pokonferencyjna"},"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G6161173764","display_name":null,"funder_award_id":"NCN UMO-2020/02/Y/ST6/00070","funder_id":"https://openalex.org/F4320322650","funder_display_name":"Narodowym Centrum Nauki"}],"funders":[{"id":"https://openalex.org/F4320322650","display_name":"Narodowym Centrum Nauki","ror":"https://ror.org/03ha2q922"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W133617167","https://openalex.org/W231210911","https://openalex.org/W2006825483","https://openalex.org/W2064675550","https://openalex.org/W2119821739","https://openalex.org/W2144182447","https://openalex.org/W2186195051","https://openalex.org/W2282821441","https://openalex.org/W2296719434","https://openalex.org/W2319759828","https://openalex.org/W2662684858","https://openalex.org/W2766736793","https://openalex.org/W2788403449","https://openalex.org/W2791987562","https://openalex.org/W2874136421","https://openalex.org/W2885195348","https://openalex.org/W2906498146","https://openalex.org/W2907577768","https://openalex.org/W2944675392","https://openalex.org/W2962819609","https://openalex.org/W3032537708","https://openalex.org/W3043826710","https://openalex.org/W3049226960","https://openalex.org/W3092385390","https://openalex.org/W3098805155","https://openalex.org/W3111082827","https://openalex.org/W3128452405","https://openalex.org/W3146308142","https://openalex.org/W3171028779","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W4295313945","https://openalex.org/W4402843978","https://openalex.org/W6609001106","https://openalex.org/W6746239490","https://openalex.org/W6748426178","https://openalex.org/W6753635576","https://openalex.org/W6762067330","https://openalex.org/W6784110853","https://openalex.org/W6796904398"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W4363671829","https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,53],"is":[2],"emerging":[3],"trend":[4],"in":[5,26,54,82],"manufacturing":[6],"processes":[7],"and":[8,48,60,85,101,137],"may":[9],"be":[10],"considered":[11],"as":[12,23,30,32],"part":[13],"of":[14,39,80,88,104,108,117,119,130],"the":[15,89,94,105,115,128],"Industry":[16],"4.0":[17],"revolution.":[18],"It":[19],"can":[20],"serve":[21],"both":[22,99],"diagnostic":[24],"tool":[25],"predictive":[27],"maintenance":[28],"task,":[29],"well":[31],"trace":[33],"back":[34],"mechanism":[35],"for":[36,50],"assessing":[37],"quality":[38],"production":[40],"or":[41],"services.":[42],"In":[43],"this":[44],"paper":[45],"we":[46,91],"describe":[47],"approach":[49,132],"explainable":[51],"anomaly":[52],"industrial":[55,145],"data":[56,140],"which":[57,97],"contains":[58],"sequential":[59],"static":[61],"features.":[62],"We":[63,126],"based":[64],"our":[65,131],"solution":[66],"on":[67,133,138],"modified":[68],"autoencoder":[69],"architecture":[70],"with":[71],"Long":[72],"Short-Term":[73],"Memory":[74],"layers.":[75],"To":[76],"address":[77],"a":[78],"problem":[79],"explinability":[81],"deep":[83,123],"learning":[84,124],"find":[86],"origin":[87],"anomalies":[90,120],"have":[92],"engaged":[93],"SHAP":[95,109],"method,":[96],"gives":[98],"local":[100],"global":[102],"explanations":[103,110],"model.":[106,125],"Analysis":[107],"allowed":[111],"us":[112],"to":[113],"determine":[114],"source":[116],"majority":[118],"detected":[121],"by":[122],"demonstrated":[127],"feasibility":[129],"synthetic,":[134],"reproducible":[135],"dataset":[136],"real-life":[139],"gathered":[141],"from":[142],"hot":[143],"rolling":[144],"process.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}