{"id":"https://openalex.org/W4313824269","doi":"https://doi.org/10.1080/0951192x.2022.2163295","title":"Predicting volumetric error compensation for five-axis machine tool using machine learning","display_name":"Predicting volumetric error compensation for five-axis machine tool using machine learning","publication_year":2023,"publication_date":"2023-01-09","ids":{"openalex":"https://openalex.org/W4313824269","doi":"https://doi.org/10.1080/0951192x.2022.2163295"},"language":"en","primary_location":{"id":"doi:10.1080/0951192x.2022.2163295","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0951192x.2022.2163295","pdf_url":null,"source":{"id":"https://openalex.org/S57062392","display_name":"International Journal of Computer Integrated Manufacturing","issn_l":"0951-192X","issn":["0951-192X","1362-3052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Integrated Manufacturing","raw_type":"journal-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/A5071455766","display_name":"Van-Hai Nguyen","orcid":"https://orcid.org/0000-0002-5959-1883"},"institutions":[{"id":"https://openalex.org/I4210111036","display_name":"Phenikaa (Vietnam)","ror":"https://ror.org/0250p1d07","country_code":"VN","type":"company","lineage":["https://openalex.org/I4210111036"]},{"id":"https://openalex.org/I4210124651","display_name":"Phenikaa University","ror":"https://ror.org/03anxx281","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210124651"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van-Hai Nguyen","raw_affiliation_strings":["Faculty of Mechanical Engineering and Mechatronics, PHENIKAA University, Ha Dong, Hanoi, Vietnam","PHENIKAA Research and Technology Institute (PRATI), A&A Green Phoenix Group JSC, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"Faculty of Mechanical Engineering and Mechatronics, PHENIKAA University, Ha Dong, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210124651"]},{"raw_affiliation_string":"PHENIKAA Research and Technology Institute (PRATI), A&A Green Phoenix Group JSC, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210111036"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024957412","display_name":"Tien-Thinh Le","orcid":"https://orcid.org/0000-0002-1603-5000"},"institutions":[{"id":"https://openalex.org/I4210111036","display_name":"Phenikaa (Vietnam)","ror":"https://ror.org/0250p1d07","country_code":"VN","type":"company","lineage":["https://openalex.org/I4210111036"]},{"id":"https://openalex.org/I4210124651","display_name":"Phenikaa University","ror":"https://ror.org/03anxx281","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210124651"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Tien-Thinh Le","raw_affiliation_strings":["Faculty of Mechanical Engineering and Mechatronics, PHENIKAA University, Ha Dong, Hanoi, Vietnam","PHENIKAA Research and Technology Institute (PRATI), A&A Green Phoenix Group JSC, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"Faculty of Mechanical Engineering and Mechatronics, PHENIKAA University, Ha Dong, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210124651"]},{"raw_affiliation_string":"PHENIKAA Research and Technology Institute (PRATI), A&A Green Phoenix Group JSC, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210111036"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018462188","display_name":"Hoanh-Son Truong","orcid":null},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hoanh-Son Truong","raw_affiliation_strings":["School of Mechanical Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014154447","display_name":"Huan Thanh Duong","orcid":"https://orcid.org/0000-0002-2045-7759"},"institutions":[{"id":"https://openalex.org/I4210102522","display_name":"Vietnam National University of Agriculture","ror":"https://ror.org/01abaah21","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210102522"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huan Thanh Duong","raw_affiliation_strings":["Faculty of Engineering, Vietnam National University of Agriculture, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Vietnam National University of Agriculture, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210102522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102009917","display_name":"Minh Vuong Le","orcid":"https://orcid.org/0000-0003-0631-656X"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210160945","display_name":"Laboratoire Mod\u00e9lisation et Simulation Multi-Echelle","ror":"https://ror.org/04rrzfd14","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I197681013","https://openalex.org/I4210095849","https://openalex.org/I4210154111","https://openalex.org/I4210160945"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Minh Vuong Le","raw_affiliation_strings":["Laboratoire Mod\u00e9lisation et Simulation Multi Echelle, Universit\u00e9 Paris-Est, MSME UMR 8208 CNRS, Marne-la-Vall\u00e9e, France"],"affiliations":[{"raw_affiliation_string":"Laboratoire Mod\u00e9lisation et Simulation Multi Echelle, Universit\u00e9 Paris-Est, MSME UMR 8208 CNRS, Marne-la-Vall\u00e9e, France","institution_ids":["https://openalex.org/I4210160945","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5024957412"],"corresponding_institution_ids":["https://openalex.org/I4210111036","https://openalex.org/I4210124651"],"apc_list":null,"apc_paid":null,"fwci":2.7285,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.89660232,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"36","issue":"8","first_page":"1191","last_page":"1218"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11583","display_name":"Advanced Measurement and Metrology Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11583","display_name":"Advanced Measurement and Metrology Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10188","display_name":"Advanced machining processes and optimization","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/mean-squared-error","display_name":"Mean squared error","score":0.692104697227478},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6612073183059692},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6285663843154907},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5883910059928894},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5715221166610718},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.552070677280426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5026853084564209},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.49686554074287415},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.49543750286102295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47247692942619324},{"id":"https://openalex.org/keywords/proper-linear-model","display_name":"Proper linear model","score":0.4720041751861572},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45355018973350525},{"id":"https://openalex.org/keywords/coefficient-of-determination","display_name":"Coefficient of determination","score":0.45221439003944397},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4490101635456085},{"id":"https://openalex.org/keywords/machine-tool","display_name":"Machine tool","score":0.41555255651474},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39622628688812256},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3409702181816101},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1698727011680603}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.692104697227478},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6612073183059692},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6285663843154907},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5883910059928894},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5715221166610718},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.552070677280426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5026853084564209},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.49686554074287415},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.49543750286102295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47247692942619324},{"id":"https://openalex.org/C32224588","wikidata":"https://www.wikidata.org/wiki/Q7250175","display_name":"Proper linear model","level":4,"score":0.4720041751861572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45355018973350525},{"id":"https://openalex.org/C128990827","wikidata":"https://www.wikidata.org/wiki/Q192830","display_name":"Coefficient of determination","level":2,"score":0.45221439003944397},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4490101635456085},{"id":"https://openalex.org/C5941749","wikidata":"https://www.wikidata.org/wiki/Q19768","display_name":"Machine tool","level":2,"score":0.41555255651474},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39622628688812256},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3409702181816101},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1698727011680603},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/0951192x.2022.2163295","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0951192x.2022.2163295","pdf_url":null,"source":{"id":"https://openalex.org/S57062392","display_name":"International Journal of Computer Integrated Manufacturing","issn_l":"0951-192X","issn":["0951-192X","1362-3052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Integrated Manufacturing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W1848211986","https://openalex.org/W1964952728","https://openalex.org/W1969291558","https://openalex.org/W1970360626","https://openalex.org/W1971722730","https://openalex.org/W1976232313","https://openalex.org/W1979777795","https://openalex.org/W1988268292","https://openalex.org/W1991312425","https://openalex.org/W1997145766","https://openalex.org/W2002106300","https://openalex.org/W2005403012","https://openalex.org/W2007424489","https://openalex.org/W2009169944","https://openalex.org/W2012569707","https://openalex.org/W2013373507","https://openalex.org/W2022248687","https://openalex.org/W2056955527","https://openalex.org/W2062756384","https://openalex.org/W2064179326","https://openalex.org/W2069125244","https://openalex.org/W2081149604","https://openalex.org/W2081816605","https://openalex.org/W2086209297","https://openalex.org/W2088730795","https://openalex.org/W2093139468","https://openalex.org/W2095367669","https://openalex.org/W2097486709","https://openalex.org/W2136463933","https://openalex.org/W2139408969","https://openalex.org/W2165495257","https://openalex.org/W2193270734","https://openalex.org/W2267186426","https://openalex.org/W2295598076","https://openalex.org/W2328212276","https://openalex.org/W2404559802","https://openalex.org/W2480645619","https://openalex.org/W2492328074","https://openalex.org/W2509736658","https://openalex.org/W2514088228","https://openalex.org/W2544883878","https://openalex.org/W2552806983","https://openalex.org/W2588155803","https://openalex.org/W2604808181","https://openalex.org/W2771639008","https://openalex.org/W2781702232","https://openalex.org/W2789282145","https://openalex.org/W2887719843","https://openalex.org/W2894782227","https://openalex.org/W2898864091","https://openalex.org/W2911455822","https://openalex.org/W2911964244","https://openalex.org/W2912361013","https://openalex.org/W2952297896","https://openalex.org/W2953121811","https://openalex.org/W2972457185","https://openalex.org/W2990039880","https://openalex.org/W2993424960","https://openalex.org/W2994669395","https://openalex.org/W3012194931","https://openalex.org/W3022199973","https://openalex.org/W3024877203","https://openalex.org/W3044339716","https://openalex.org/W3092093369","https://openalex.org/W3095807143","https://openalex.org/W3099426638","https://openalex.org/W3119610934","https://openalex.org/W3123920941","https://openalex.org/W3135524811","https://openalex.org/W3135609456","https://openalex.org/W3174058747","https://openalex.org/W3198484697","https://openalex.org/W3201751510","https://openalex.org/W4230674625","https://openalex.org/W4235922964","https://openalex.org/W4239510810","https://openalex.org/W4251364655","https://openalex.org/W4281649841","https://openalex.org/W4309580848"],"related_works":["https://openalex.org/W206160466","https://openalex.org/W2886532972","https://openalex.org/W1685088304","https://openalex.org/W2743208879","https://openalex.org/W600390644","https://openalex.org/W2066533688","https://openalex.org/W1557089904","https://openalex.org/W4391071549","https://openalex.org/W623416330","https://openalex.org/W1769516736"],"abstract_inverted_index":{"This":[0],"work":[1],"proposes":[2],"a":[3,15],"rapid":[4],"and":[5,40,47,58,93,156,194],"robust":[6],"machine-learning":[7],"model":[8,66,76,127],"to":[9,52,59,62,130,139],"predict":[10],"the":[11,56,64,68,102,114,117,121,124,132,140,144,150,168,174],"volumetric":[12],"error":[13],"of":[14,74,95,164],"five-axis":[16],"machine":[17,23],"tool.":[18],"For":[19],"this":[20,106,197],"purpose,":[21],"several":[22],"learning":[24],"models":[25,54,103],"\u2013":[26,43],"which":[27],"are":[28,108],"MultiOutput":[29,32],"regression,":[30,33,35,37],"Chained":[31],"Linear":[34],"SVM":[36],"XGB":[38],"regression":[39,42],"ANN":[41],"have":[44],"been":[45,181,190],"selected,":[46],"their":[48],"performances":[49],"were":[50],"compared":[51],"other":[53],"in":[55,105,113,143,192,196],"literature":[57,145],"one":[60],"another":[61],"find":[63],"best":[65,175],"for":[67,167,183],"problem":[69],"at":[70],"hand.":[71],"The":[72,98],"robustness":[73],"each":[75],"is":[77],"investigated":[78],"using":[79,116],"three":[80],"statistical":[81,136],"metrics:":[82],"namely":[83],"Root":[84],"Mean":[85,89],"Square":[86],"Error":[87,91],"(RMSE),":[88],"Absolute":[90],"(MAE)":[92],"Coefficient":[94],"Determination":[96],"(R2).":[97],"results":[99],"show":[100],"that":[101],"proposed":[104,122,152],"paper":[107],"more":[109],"effective":[110],"than":[111],"those":[112],"literature,":[115],"same":[118],"data.":[119],"Amongst":[120],"models,":[123],"SVR":[125,169],"Regression":[126],"has":[128,180,189],"proven":[129],"be":[131],"best,":[133],"considering":[134],"all":[135],"metrics.":[137],"Compared":[138],"polynomial":[141],"method":[142,151],"with":[146,161],"varying":[147],"order":[148],"levels,":[149],"here":[153],"improves":[154],"accuracy":[155],"predictive":[157],"performance":[158],"by":[159],"27%,":[160],"an":[162,177],"RMSE":[163],"0.03246":[165],"mm":[166],"model.":[170],"Finally,":[171],"based":[172],"on":[173],"model,":[176],"explicit":[178],"equation":[179,188],"deduced":[182],"practical":[184],"applications.":[185],"That":[186],"prediction":[187],"implemented":[191],"Excel":[193],"included":[195],"paper.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
