{"id":"https://openalex.org/W2533099810","doi":"https://doi.org/10.1109/etfa.2014.7005357","title":"Predictive maintenance decision using statistical linear regression and kernel methods","display_name":"Predictive maintenance decision using statistical linear regression and kernel methods","publication_year":2014,"publication_date":"2014-09-01","ids":{"openalex":"https://openalex.org/W2533099810","doi":"https://doi.org/10.1109/etfa.2014.7005357","mag":"2533099810"},"language":"en","primary_location":{"id":"doi:10.1109/etfa.2014.7005357","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2014.7005357","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)","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/A5113546508","display_name":"Tung Le","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Tung Le","raw_affiliation_strings":["Manufacturing Execution and Control Group, SIMTech, Singapore"],"affiliations":[{"raw_affiliation_string":"Manufacturing Execution and Control Group, SIMTech, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101440398","display_name":"Ming Luo","orcid":"https://orcid.org/0000-0002-6156-6230"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ming Luo","raw_affiliation_strings":["Manufacturing Execution and Control Group, SIMTech, Singapore"],"affiliations":[{"raw_affiliation_string":"Manufacturing Execution and Control Group, SIMTech, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110472018","display_name":"Jun-Hong Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Junhong Zhou","raw_affiliation_strings":["Manufacturing Execution and Control Group, SIMTech, Singapore"],"affiliations":[{"raw_affiliation_string":"Manufacturing Execution and Control Group, SIMTech, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108612422","display_name":"Hian Leng Chan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Hian L. Chan","raw_affiliation_strings":["Manufacturing Execution and Control Group, SIMTech, Singapore"],"affiliations":[{"raw_affiliation_string":"Manufacturing Execution and Control Group, SIMTech, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113546508"],"corresponding_institution_ids":["https://openalex.org/I4210091207"],"apc_list":null,"apc_paid":null,"fwci":2.9002,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.91229602,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.9919999837875366,"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":0.9919000267982483,"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":0.5937118530273438},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5587514638900757},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5579927563667297},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5431777834892273},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.53360515832901},{"id":"https://openalex.org/keywords/predictive-maintenance","display_name":"Predictive maintenance","score":0.5322387218475342},{"id":"https://openalex.org/keywords/preventive-maintenance","display_name":"Preventive maintenance","score":0.4649542570114136},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.37298083305358887},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3453986942768097},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32223036885261536},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2498583197593689},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2288510501384735}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5937118530273438},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5587514638900757},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5579927563667297},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5431777834892273},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.53360515832901},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.5322387218475342},{"id":"https://openalex.org/C24090081","wikidata":"https://www.wikidata.org/wiki/Q1043452","display_name":"Preventive maintenance","level":2,"score":0.4649542570114136},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.37298083305358887},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3453986942768097},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32223036885261536},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2498583197593689},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2288510501384735},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/etfa.2014.7005357","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2014.7005357","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W110314235","https://openalex.org/W1588861010","https://openalex.org/W1603749820","https://openalex.org/W1680392829","https://openalex.org/W1975322338","https://openalex.org/W1976084415","https://openalex.org/W1977132434","https://openalex.org/W2003484186","https://openalex.org/W2009447596","https://openalex.org/W2041403689","https://openalex.org/W2045186954","https://openalex.org/W2055166298","https://openalex.org/W2152766986","https://openalex.org/W2152938409","https://openalex.org/W2161557129","https://openalex.org/W2167616055","https://openalex.org/W2171033594","https://openalex.org/W2801292233","https://openalex.org/W4233065439","https://openalex.org/W4233518571","https://openalex.org/W4255095071","https://openalex.org/W6637386731"],"related_works":["https://openalex.org/W23403803","https://openalex.org/W2063020871","https://openalex.org/W3006925589","https://openalex.org/W1969617929","https://openalex.org/W3159422131","https://openalex.org/W4210572926","https://openalex.org/W4283512660","https://openalex.org/W3195330874","https://openalex.org/W2195885512","https://openalex.org/W2028508054"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,34,79],"develop":[4],"a":[5,27,81,92,123,133],"predictive":[6],"maintenance":[7,18,125,164],"(PdM)":[8],"method":[9,94],"to":[10,16,19,26,39,59,63,70,85,95,151,167],"determine":[11],"the":[12,41,47,65,97,103,107,115,118,139,144,152,168],"most":[13],"effective":[14],"time":[15],"apply":[17,36,91],"an":[20,61],"equipment":[21,43],"and":[22,90,158],"study":[23],"its":[24],"application":[25],"real":[28,130],"semiconductor":[29,134],"etching":[30,135],"chamber.":[31],"More":[32],"specifically,":[33],"first":[35],"linear":[37,54,147,156],"regression":[38,148],"predict":[40],"(output)":[42],"health":[44,120],"condition":[45,121],"from":[46,132],"(input)":[48],"operational":[49,68],"parameters.":[50],"This":[51],"choice":[52],"of":[53,67,102,117,171],"model":[55,157],"also":[56],"allows":[57],"us":[58],"propose":[60],"algorithm":[62],"reduce":[64],"number":[66],"parameters":[69],"be":[71,111,160],"monitored":[72],"for":[73,162],"PdM":[74,108,141],"purposes":[75],"using":[76,129,154],"t-statistics.":[77],"Then,":[78],"follow":[80],"cross-validation":[82],"based":[83,113],"procedure":[84],"generate":[86],"prediction":[87,104],"error":[88],"samples":[89],"kernel":[93],"construct":[96],"corresponding":[98],"probability":[99],"density":[100],"function":[101],"error.":[105],"Finally,":[106],"decision":[109,142],"can":[110,159],"made":[112],"on":[114],"likelihood":[116],"predicted":[119],"exceeding":[122],"certain":[124],"threshold.":[126],"Our":[127],"analysis":[128],"data":[131],"chamber":[136],"shows":[137],"that":[138],"proposed":[140],"with":[143],"reduced":[145],"dimension":[146],"performs":[149],"comparably":[150],"one":[153],"full-scale":[155],"used":[161],"better":[163],"planning":[165],"compared":[166],"existing":[169],"practice":[170],"fixed-schedule":[172],"maintenance.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
