{"id":"https://openalex.org/W2805477443","doi":"https://doi.org/10.1109/ictai.2017.00082","title":"Combining Process Mining with Trace Clustering: Manufacturing Shop Floor Process - An Applied Case","display_name":"Combining Process Mining with Trace Clustering: Manufacturing Shop Floor Process - An Applied Case","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2805477443","doi":"https://doi.org/10.1109/ictai.2017.00082","mag":"2805477443"},"language":"en","primary_location":{"id":"doi:10.1109/ictai.2017.00082","doi":"https://doi.org/10.1109/ictai.2017.00082","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai.2017.00082","pdf_url":null,"source":{"id":"https://openalex.org/S4210176007","display_name":"IEEE International Conference on Tools with Artificial Intelligence (ICTAI)","issn_l":"1082-3409","issn":["1082-3409","2375-0197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI)","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/A5064883511","display_name":"Alex Meincheim","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alex Meincheim","raw_affiliation_strings":["Information Technology Department, Weg Equipamentos El\u00e9tricos, S/A Jaragu\u00e1 do Sul, SC, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Technology Department, Weg Equipamentos El\u00e9tricos, S/A Jaragu\u00e1 do Sul, SC, Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020494341","display_name":"Cleiton dos Santos Garcia","orcid":"https://orcid.org/0000-0002-9037-4481","observed_orcids":["https://orcid.org/0000-0002-9037-4481"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cleiton dos Santos Garcia","raw_affiliation_strings":["Inf. Technol. Dept., Weg Equipamentos, Jaragu\u00e1 do Sul, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inf. Technol. Dept., Weg Equipamentos, Jaragu\u00e1 do Sul, Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008799936","display_name":"J\u00falio C\u00e9sar Nievola","orcid":"https://orcid.org/0000-0002-2212-4499","observed_orcids":["https://orcid.org/0000-0002-2212-4499"]},"institutions":[{"id":"https://openalex.org/I176838256","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1","ror":"https://ror.org/02x1vjk79","country_code":"BR","type":"education","lineage":["https://openalex.org/I176838256"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Julio Cesar Nievola","raw_affiliation_strings":["Pontificia Universidade Catolica do Parana, Curitiba, PR, BR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pontificia Universidade Catolica do Parana, Curitiba, PR, BR","institution_ids":["https://openalex.org/I176838256"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082099991","display_name":"Edson Em\u00edlio Scalabrin","orcid":"https://orcid.org/0000-0002-3918-1799","observed_orcids":["https://orcid.org/0000-0002-3918-1799"]},"institutions":[{"id":"https://openalex.org/I176838256","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1","ror":"https://ror.org/02x1vjk79","country_code":"BR","type":"education","lineage":["https://openalex.org/I176838256"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Edson Emfilio Scalabrin","raw_affiliation_strings":["Pontificia Universidade Catolica do Parana, Curitiba, PR, BR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pontificia Universidade Catolica do Parana, Curitiba, PR, BR","institution_ids":["https://openalex.org/I176838256"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4844,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.81328486,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"498","last_page":"505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11125","display_name":"Petri Nets in System Modeling","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/process-mining","display_name":"process mining","score":0.9929999709129333},{"id":"https://openalex.org/keywords/trace-clustering","display_name":"trace clustering","score":0.9990000128746033},{"id":"https://openalex.org/keywords/process-discovery","display_name":"process discovery","score":0.6320000290870667},{"id":"https://openalex.org/keywords/process-model-complexity","display_name":"process model complexity","score":0.5099999904632568},{"id":"https://openalex.org/keywords/process-variants","display_name":"process variants","score":0.6990000009536743},{"id":"https://openalex.org/keywords/production-performance-indicators","display_name":"production performance indicators","score":0.7900000214576721},{"id":"https://openalex.org/keywords/bottlenecks","display_name":"bottlenecks","score":0.8629999756813049},{"id":"https://openalex.org/keywords/process-improvement","display_name":"process improvement","score":0.8640000224113464}],"concepts":[{"id":"https://openalex.org/C124670913","wikidata":"https://www.wikidata.org/wiki/Q2608526","display_name":"Process mining","level":5,"score":0.8785479664802551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7714093923568726},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.7058608531951904},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.6897580027580261},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5993667244911194},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.5972654223442078},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.5947974324226379},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.590988278388977},{"id":"https://openalex.org/C93453677","wikidata":"https://www.wikidata.org/wiki/Q1017580","display_name":"Business process discovery","level":5,"score":0.5384905338287354},{"id":"https://openalex.org/C174998907","wikidata":"https://www.wikidata.org/wiki/Q357662","display_name":"Work in process","level":2,"score":0.4482206106185913},{"id":"https://openalex.org/C80309976","wikidata":"https://www.wikidata.org/wiki/Q7007379","display_name":"Business process management","level":4,"score":0.4481036067008972},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.44805383682250977},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.4443361163139343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4418802261352539},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4189060628414154},{"id":"https://openalex.org/C85345410","wikidata":"https://www.wikidata.org/wiki/Q851587","display_name":"Business process","level":3,"score":0.37102869153022766},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3571752905845642},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.32362931966781616},{"id":"https://openalex.org/C207505557","wikidata":"https://www.wikidata.org/wiki/Q4374012","display_name":"Business process modeling","level":4,"score":0.2927491068840027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25179070234298706},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15531393885612488},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictai.2017.00082","doi":"https://doi.org/10.1109/ictai.2017.00082","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai.2017.00082","pdf_url":null,"source":{"id":"https://openalex.org/S4210176007","display_name":"IEEE International Conference on Tools with Artificial Intelligence (ICTAI)","issn_l":"1082-3409","issn":["1082-3409","2375-0197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.651199996471405}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1497007062","https://openalex.org/W1514774939","https://openalex.org/W1563871563","https://openalex.org/W1578876701","https://openalex.org/W1598798710","https://openalex.org/W1964516842","https://openalex.org/W1985114523","https://openalex.org/W1992419399","https://openalex.org/W2006155284","https://openalex.org/W2015317855","https://openalex.org/W2042759024","https://openalex.org/W2043164102","https://openalex.org/W2047107323","https://openalex.org/W2094132988","https://openalex.org/W2096998948","https://openalex.org/W2098250644","https://openalex.org/W2107620109","https://openalex.org/W2113280469","https://openalex.org/W2150042906","https://openalex.org/W2155862563","https://openalex.org/W2158891129","https://openalex.org/W2163284032","https://openalex.org/W2168477321","https://openalex.org/W2170917993","https://openalex.org/W2371622980","https://openalex.org/W2404847665","https://openalex.org/W2593991087","https://openalex.org/W4243932450","https://openalex.org/W6713330303"],"related_works":["https://openalex.org/W2159493330","https://openalex.org/W2163284032","https://openalex.org/W2133984821","https://openalex.org/W3202975295","https://openalex.org/W4376607195","https://openalex.org/W7100031930","https://openalex.org/W1878235097","https://openalex.org/W7096853470","https://openalex.org/W2786666982","https://openalex.org/W4386460481"],"abstract_inverted_index":{"Process":[0],"mining":[1,29],"allows":[2],"observing":[3],"process":[4,28,49,69,90,107,120,142],"execution":[5],"based":[6],"on":[7],"real":[8],"event":[9],"data":[10],"and":[11,14,24,71,75,91,122,138],"proposes":[12],"methods":[13],"tools":[15],"to":[16,54,103,140],"provide":[17],"diagnostics,":[18],"reducing":[19,65],"the":[20,42,66,73,106,128],"gaps":[21],"between":[22],"practice":[23],"conceptual":[25],"models.":[26],"When":[27],"discovery":[30],"techniques":[31,100],"are":[32,44,52],"applied":[33,81],"in":[34,83,93,109],"flexible":[35],"processes":[36],"with":[37,87],"many":[38,112],"decisions":[39,135],"at":[40,136],"runtime,":[41],"results":[43,129],"often":[45],"semi-structured":[46],"or":[47],"unstructured":[48,89],"models":[50,70],"that":[51],"difficult":[53],"understand.":[55],"In":[56],"this":[57],"context,":[58],"trace":[59,113],"clustering":[60],"is":[61],"an":[62,80,88],"approach":[63],"for":[64],"complexity":[67],"of":[68,99],"improving":[72],"accuracy":[74],"comprehensibility.":[76],"This":[77],"paper":[78],"presents":[79],"case":[82],"industrial":[84],"manufacturing":[85],"production":[86,94,125],"issues":[92],"performance":[95],"indicators.":[96],"A":[97],"set":[98],"were":[101],"used":[102],"understand":[104],"how":[105,111],"occurs":[108],"practice,":[110],"clusters":[114],"should":[115],"be":[116],"identified":[117],"as":[118],"homogeneous":[119],"variants,":[121],"what":[123],"causes":[124],"inefficiency.":[126],"Finally,":[127],"identify":[130],"bottlenecks":[131],"caused":[132],"by":[133],"erroneous":[134],"runtime":[137],"serve":[139],"support":[141],"improvement.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2018-06-13T00:00:00"}