{"id":"https://openalex.org/W4352981500","doi":"https://doi.org/10.1109/icsrs56243.2022.10067554","title":"Comparison of Artificial Neural Network Technique-Based Failure Predictions of Mechanical Components","display_name":"Comparison of Artificial Neural Network Technique-Based Failure Predictions of Mechanical Components","publication_year":2022,"publication_date":"2022-11-23","ids":{"openalex":"https://openalex.org/W4352981500","doi":"https://doi.org/10.1109/icsrs56243.2022.10067554"},"language":"en","primary_location":{"id":"doi:10.1109/icsrs56243.2022.10067554","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsrs56243.2022.10067554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 6th International Conference on System Reliability and Safety (ICSRS)","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/A5075698208","display_name":"Basheer Shaheen","orcid":"https://orcid.org/0000-0002-1241-2198"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Basheer Shaheen","raw_affiliation_strings":["Budapest University of Technology and Economics,Department of Manufacturing Science and Engineering,Budapest,Hungary","Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics, Budapest, Hungary"],"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Department of Manufacturing Science and Engineering,Budapest,Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016931649","display_name":"Istv\u00e1n N\u00e9meth","orcid":"https://orcid.org/0000-0001-7122-3891"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Istv\u00e1n N\u00e9meth","raw_affiliation_strings":["Budapest University of Technology and Economics,Department of Manufacturing Science and Engineering,Budapest,Hungary","Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics, Budapest, Hungary"],"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Department of Manufacturing Science and Engineering,Budapest,Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008223908","display_name":"\u00c1d\u00e1m Kocsis","orcid":null},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"\u00c1d\u00e1m Kocsis","raw_affiliation_strings":["Budapest University of Technology and Economics,Department of Manufacturing Science and Engineering,Budapest,Hungary","Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics, Budapest, Hungary"],"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Department of Manufacturing Science and Engineering,Budapest,Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075698208"],"corresponding_institution_ids":["https://openalex.org/I29770179"],"apc_list":null,"apc_paid":null,"fwci":0.1205,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45644721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"33","issue":null,"first_page":"94","last_page":"98"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.989799976348877,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.989799976348877,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9758999943733215,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9746000170707703,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.8039488792419434},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7038664221763611},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6043959259986877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4960115849971771},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4273586869239807},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23865291476249695}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.8039488792419434},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7038664221763611},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6043959259986877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4960115849971771},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4273586869239807},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23865291476249695},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsrs56243.2022.10067554","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icsrs56243.2022.10067554","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 6th International Conference on System Reliability and Safety (ICSRS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W176292746","https://openalex.org/W1977002251","https://openalex.org/W2019282798","https://openalex.org/W2030678516","https://openalex.org/W2083513507","https://openalex.org/W2096538674","https://openalex.org/W2107805444","https://openalex.org/W2110221383","https://openalex.org/W2133764509","https://openalex.org/W2464234006","https://openalex.org/W2737886213","https://openalex.org/W2971978239","https://openalex.org/W2972137370","https://openalex.org/W3023666196","https://openalex.org/W3082059091","https://openalex.org/W3111634880","https://openalex.org/W3128690092","https://openalex.org/W4221117073","https://openalex.org/W4281560503","https://openalex.org/W4307261888","https://openalex.org/W6730237435","https://openalex.org/W6741549204","https://openalex.org/W6755503919"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3209574120","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Failure":[0],"prediction":[1,61,77,104],"is":[2,49,67],"considered":[3],"one":[4],"of":[5,19,33,54,94],"the":[6,30,52,80,86,90,103,107,113],"most":[7],"critical":[8],"methods":[9],"for":[10],"prognostic":[11],"health":[12],"management":[13],"and":[14,17,28,60,79,106,116],"maintenance":[15,114],"planning":[16],"scheduling":[18],"manufacturing":[20,101],"systems.":[21],"This":[22,46],"article":[23],"presents":[24],"a":[25,64,70],"comparative":[26,47],"analysis":[27,48],"shows":[29],"main":[31],"characteristics":[32],"different":[34,55],"artificial":[35,73],"neural":[36,74],"network":[37,56],"approaches":[38],"used":[39],"to":[40,97,111],"predict":[41],"failures":[42],"in":[43,92],"mechanical":[44],"components.":[45],"based":[50],"on":[51],"use":[53],"architectures,":[57],"training":[58],"algorithms,":[59],"results.":[62],"Also,":[63],"brief":[65],"comparison":[66],"conducted":[68],"between":[69],"newly":[71],"developed":[72,82],"network-based":[75],"failure":[76],"algorithm":[78,88],"previously":[81],"models":[83],"confirming":[84],"that":[85],"new":[87],"outperforms":[89],"others":[91],"terms":[93],"its":[95],"ability":[96],"deal":[98],"with":[99],"complex":[100],"systems,":[102],"accuracy,":[105],"early":[108],"predictions":[109],"required":[110],"improve":[112],"plans":[115],"schedules.":[117]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
