{"id":"https://openalex.org/W4407736315","doi":"https://doi.org/10.1109/access.2025.3543600","title":"Methodology for Commercial Vehicle Mechanical Systems Maintenance: Data-Driven and Deep-Learning-Based Prediction","display_name":"Methodology for Commercial Vehicle Mechanical Systems Maintenance: Data-Driven and Deep-Learning-Based Prediction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407736315","doi":"https://doi.org/10.1109/access.2025.3543600"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3543600","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3543600","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3543600","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034865990","display_name":"R\u00f4mulo Gon\u00e7alves Lins","orcid":"https://orcid.org/0000-0001-9878-0081"},"institutions":[{"id":"https://openalex.org/I71715416","display_name":"Universidade Federal do ABC","ror":"https://ror.org/028kg9j04","country_code":"BR","type":"education","lineage":["https://openalex.org/I71715416"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Romulo Gon\u00e7alves Lins","raw_affiliation_strings":["Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil"],"affiliations":[{"raw_affiliation_string":"Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil","institution_ids":["https://openalex.org/I71715416"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112318967","display_name":"Tiago Nascimento De Freitas","orcid":null},"institutions":[{"id":"https://openalex.org/I71715416","display_name":"Universidade Federal do ABC","ror":"https://ror.org/028kg9j04","country_code":"BR","type":"education","lineage":["https://openalex.org/I71715416"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Tiago Nascimento de Freitas","raw_affiliation_strings":["Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil"],"affiliations":[{"raw_affiliation_string":"Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil","institution_ids":["https://openalex.org/I71715416"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060035820","display_name":"Ricardo Gaspar","orcid":"https://orcid.org/0000-0002-7336-6308"},"institutions":[{"id":"https://openalex.org/I71715416","display_name":"Universidade Federal do ABC","ror":"https://ror.org/028kg9j04","country_code":"BR","type":"education","lineage":["https://openalex.org/I71715416"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ricardo Gaspar","raw_affiliation_strings":["Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil"],"affiliations":[{"raw_affiliation_string":"Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil","institution_ids":["https://openalex.org/I71715416"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034865990"],"corresponding_institution_ids":["https://openalex.org/I71715416"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.9966,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.92380553,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"33799","last_page":"33812"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.6692000031471252,"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"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.6692000031471252,"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/computer-science","display_name":"Computer science","score":0.6295724511146545},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4839392304420471},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.44451791048049927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42680519819259644},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.3639923334121704},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15588942170143127},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12633579969406128}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6295724511146545},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4839392304420471},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.44451791048049927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42680519819259644},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.3639923334121704},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15588942170143127},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12633579969406128}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3543600","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3543600","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:45d6625d1d7c42aaaef9f6aac6ba5266","is_oa":true,"landing_page_url":"https://doaj.org/article/45d6625d1d7c42aaaef9f6aac6ba5266","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 33799-33812 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3543600","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3543600","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G8553358939","display_name":null,"funder_award_id":"303527/2021-8","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2039125545","https://openalex.org/W2064675550","https://openalex.org/W2084652808","https://openalex.org/W2131774270","https://openalex.org/W2148143831","https://openalex.org/W2530071817","https://openalex.org/W2533924129","https://openalex.org/W2765742249","https://openalex.org/W2788370604","https://openalex.org/W2795099492","https://openalex.org/W2912412502","https://openalex.org/W2955414983","https://openalex.org/W2970347295","https://openalex.org/W2972137370","https://openalex.org/W3003513033","https://openalex.org/W3212409379","https://openalex.org/W3217689614","https://openalex.org/W4200433233","https://openalex.org/W4220848465","https://openalex.org/W4292980865","https://openalex.org/W4310614412","https://openalex.org/W4319081211","https://openalex.org/W4319996333","https://openalex.org/W4324325019","https://openalex.org/W4366966689","https://openalex.org/W4390493401","https://openalex.org/W4390659195","https://openalex.org/W6609413780","https://openalex.org/W6856526273"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,83],"predictive":[4],"maintenance":[5,25],"(PdM)":[6],"strategy":[7],"for":[8,117],"commercial":[9],"vehicles,":[10],"focusing":[11],"on":[12,71],"the":[13,30,107],"turbocharger\u2014a":[14],"critical":[15],"yet":[16],"often":[17],"under-monitored":[18],"component.":[19],"By":[20],"combining":[21],"sensor":[22],"signals,":[23],"workshop":[24],"logs,":[26],"and":[27,47,58,64,82,113],"technical":[28],"specifications,":[29],"study":[31],"demonstrates":[32],"how":[33],"data-driven":[34],"deep-learning":[35],"techniques":[36],"can":[37],"robustly":[38],"identify":[39],"pending":[40],"failures.":[41,95],"Specifically,":[42],"Long":[43],"Short-Term":[44],"Memory":[45],"(LSTM)":[46],"Bidirectional":[48],"LSTM":[49],"(BiLSTM)":[50],"architectures":[51],"were":[52],"employed":[53],"to":[54],"capture":[55],"temporal":[56],"dependencies":[57],"detect":[59],"patterns":[60],"that":[61,76],"conventional":[62],"approaches":[63],"purely":[65],"onboard":[66],"monitoring":[67],"might":[68],"overlook.":[69],"Results":[70],"real-world":[72],"fleet":[73],"data":[74,112],"indicate":[75],"BiLSTM":[77,97],"achieved":[78],"higher":[79,100],"recall":[80],"(98.65%)":[81],"lower":[84],"cost-score":[85],"than":[86],"standard":[87],"LSTM,":[88],"highlighting":[89],"its":[90,103],"effectiveness":[91],"in":[92,121],"minimizing":[93],"missed":[94],"Although":[96],"incurred":[98],"slightly":[99],"computational":[101],"overhead,":[102],"superior":[104],"performance":[105],"underscores":[106],"value":[108],"of":[109],"integrating":[110],"multi-sourced":[111],"advanced":[114],"sequence":[115],"models":[116],"reliable,":[118],"actionable":[119],"PdM":[120],"heavy-duty":[122],"fleets.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
