{"id":"https://openalex.org/W3184573977","doi":"https://doi.org/10.1109/eit51626.2021.9491833","title":"A Consolidated Approach towards Application of Machine Learning Principles in Additive Manufacturing","display_name":"A Consolidated Approach towards Application of Machine Learning Principles in Additive Manufacturing","publication_year":2021,"publication_date":"2021-05-14","ids":{"openalex":"https://openalex.org/W3184573977","doi":"https://doi.org/10.1109/eit51626.2021.9491833","mag":"3184573977"},"language":"en","primary_location":{"id":"doi:10.1109/eit51626.2021.9491833","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit51626.2021.9491833","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Electro Information Technology (EIT)","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/A5030196845","display_name":"Ali Raza","orcid":"https://orcid.org/0000-0003-0562-0682"},"institutions":[{"id":"https://openalex.org/I1629065","display_name":"Central Michigan University","ror":"https://ror.org/02xawj266","country_code":"US","type":"education","lineage":["https://openalex.org/I1629065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Raza","raw_affiliation_strings":["School of Engineering & Technology, Central Michigan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering & Technology, Central Michigan University","institution_ids":["https://openalex.org/I1629065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034960834","display_name":"Ali Haider","orcid":"https://orcid.org/0000-0002-2110-1025"},"institutions":[{"id":"https://openalex.org/I1629065","display_name":"Central Michigan University","ror":"https://ror.org/02xawj266","country_code":"US","type":"education","lineage":["https://openalex.org/I1629065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Haider","raw_affiliation_strings":["School of Engineering & Technology, Central Michigan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering & Technology, Central Michigan University","institution_ids":["https://openalex.org/I1629065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008591422","display_name":"Waseem Haider","orcid":"https://orcid.org/0000-0003-4235-3560"},"institutions":[{"id":"https://openalex.org/I1629065","display_name":"Central Michigan University","ror":"https://ror.org/02xawj266","country_code":"US","type":"education","lineage":["https://openalex.org/I1629065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Waseem Haider","raw_affiliation_strings":["School of Engineering & Technology, Central Michigan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering & Technology, Central Michigan University","institution_ids":["https://openalex.org/I1629065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1629065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.09514679,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"264","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.9988999962806702,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9871000051498413,"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/computer-science","display_name":"Computer science","score":0.7072349190711975},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7065010070800781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6913813352584839},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6599296927452087},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6387217044830322},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5750243663787842},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5564876198768616},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.49340835213661194},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4549739360809326},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.44902336597442627},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42543062567710876},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.42080366611480713},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.41190972924232483}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7072349190711975},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7065010070800781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6913813352584839},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6599296927452087},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6387217044830322},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5750243663787842},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5564876198768616},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.49340835213661194},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4549739360809326},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.44902336597442627},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42543062567710876},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.42080366611480713},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.41190972924232483},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eit51626.2021.9491833","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eit51626.2021.9491833","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Electro Information Technology (EIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5299999713897705,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W189596042","https://openalex.org/W1596986901","https://openalex.org/W1973032475","https://openalex.org/W2100495367","https://openalex.org/W2105728138","https://openalex.org/W2118023920","https://openalex.org/W2136922672","https://openalex.org/W2161336914","https://openalex.org/W2163922914","https://openalex.org/W2250894080","https://openalex.org/W2508223510","https://openalex.org/W2559932920","https://openalex.org/W2567885395","https://openalex.org/W2619169115","https://openalex.org/W2734067773","https://openalex.org/W2758567842","https://openalex.org/W2772042717","https://openalex.org/W2791116189","https://openalex.org/W2801604453","https://openalex.org/W2803236799","https://openalex.org/W2853420878","https://openalex.org/W2886783527","https://openalex.org/W2889333773","https://openalex.org/W2899131322","https://openalex.org/W2900615132","https://openalex.org/W2901057844","https://openalex.org/W2913284394","https://openalex.org/W2921065443","https://openalex.org/W2972263106","https://openalex.org/W2990526469","https://openalex.org/W2995098893","https://openalex.org/W2999135634","https://openalex.org/W3000445559","https://openalex.org/W3004754590","https://openalex.org/W3007681970","https://openalex.org/W3016989108","https://openalex.org/W3043532440","https://openalex.org/W3090689398","https://openalex.org/W3213553391","https://openalex.org/W6607775107","https://openalex.org/W6635815790","https://openalex.org/W6675897241","https://openalex.org/W6754598612"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W1948992892","https://openalex.org/W2104657898","https://openalex.org/W1886884218","https://openalex.org/W2964954556","https://openalex.org/W4224922629","https://openalex.org/W3019910406","https://openalex.org/W4308419594"],"abstract_inverted_index":{"In":[0,120],"recent":[1],"years,":[2],"additive":[3],"manufacturing":[4],"(AM)":[5],"has":[6,42,64],"garnered":[7],"significant":[8],"attention":[9],"all":[10],"over":[11],"the":[12,16,38,46,52,114,137,140,148],"world":[13],"due":[14],"to":[15,22,36,143],"exemplary":[17],"benefits":[18],"attained":[19],"during":[20],"design":[21],"achieving":[23],"superior":[24],"part":[25],"quality.":[26],"Researchers":[27],"have":[28],"also":[29],"started":[30],"utilizing":[31],"machine":[32],"learning":[33],"(ML)":[34],"tools":[35,124],"aid":[37],"AM":[39],"process.":[40],"Emphasis":[41],"been":[43,65],"laid":[44],"on":[45,136],"availability":[47,138],"of":[48,54,61,101,106,139,150],"ample":[49],"datasets":[50],"and":[51,70,89,156],"ease":[53],"their":[55],"acquisition.":[56],"The":[57],"need":[58],"for":[59,99,118,128,159],"establishment":[60],"feature":[62],"libraries":[63],"highlighted.":[66],"Different":[67],"ML":[68,123,145,151],"techniques":[69],"associated":[71],"models":[72],"such":[73],"as":[74,110,112],"Support":[75],"Vector":[76],"Machine":[77],"(SVM),":[78],"k-Nearest":[79],"Neighbor":[80],"(k-NN),":[81],"Decision":[82],"Trees":[83],"(DT),":[84],"Deep":[85],"Convolution":[86],"Network":[87,92],"(DNN),":[88],"Convolutional":[90],"Neural":[91],"(CNN)":[93],"are":[94,125],"being":[95],"used":[96],"by":[97],"researchers":[98],"optimization":[100],"parameters,":[102],"defect":[103],"detection,":[104],"creation":[105],"online":[107],"monitoring":[108],"systems":[109],"well":[111],"predicting":[113],"powder":[115],"spreading":[116],"mechanism":[117],"AM.":[119],"fact,":[121],"most":[122],"utilized":[126],"either":[127],"classification":[129],"or":[130],"regression":[131],"purposes.":[132],"This":[133],"paper":[134],"focuses":[135],"resources":[141],"required":[142],"employ":[144],"in":[146,152,162],"AM,":[147,153],"applications":[149],"present":[154],"limitations,":[155],"potential":[157],"opportunities":[158],"extended":[160],"use":[161],"future.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
