{"id":"https://openalex.org/W4403864243","doi":"https://doi.org/10.23919/annsim61499.2024.10732237","title":"Surrogate Modelling with Deep Learning for Optimizing Manufacturing Assembly Lines","display_name":"Surrogate Modelling with Deep Learning for Optimizing Manufacturing Assembly Lines","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4403864243","doi":"https://doi.org/10.23919/annsim61499.2024.10732237"},"language":"en","primary_location":{"id":"doi:10.23919/annsim61499.2024.10732237","is_oa":false,"landing_page_url":"https://doi.org/10.23919/annsim61499.2024.10732237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Annual Modeling and Simulation Conference (ANNSIM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://imt-mines-ales.hal.science/hal-04769789/document","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106387483","display_name":"Maryam Saadi","orcid":null},"institutions":[{"id":"https://openalex.org/I112991645","display_name":"Airbus (France)","ror":"https://ror.org/023qdcg29","country_code":"FR","type":"company","lineage":["https://openalex.org/I112991645","https://openalex.org/I4210121748"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Maryam Saadi","raw_affiliation_strings":["Airbus Helicopters,Marignane,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Airbus Helicopters,Marignane,France","institution_ids":["https://openalex.org/I112991645"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106387484","display_name":"Vincent Bernier","orcid":null},"institutions":[{"id":"https://openalex.org/I112991645","display_name":"Airbus (France)","ror":"https://ror.org/023qdcg29","country_code":"FR","type":"company","lineage":["https://openalex.org/I112991645","https://openalex.org/I4210121748"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Vincent Bernier","raw_affiliation_strings":["Airbus Helicopters,Marignane,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Airbus Helicopters,Marignane,France","institution_ids":["https://openalex.org/I112991645"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046427982","display_name":"Gr\u00e9gory Zacharewicz","orcid":"https://orcid.org/0000-0001-7726-1725"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gregory Zacharewicz","raw_affiliation_strings":["IMT-Mines Ales,Laboratory for Science of Risks,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IMT-Mines Ales,Laboratory for Science of Risks,France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005169942","display_name":"Nicolas Daclin","orcid":"https://orcid.org/0000-0002-8610-1886"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nicolas Daclin","raw_affiliation_strings":["IMT-Mines Ales,Laboratory for Science of Risks,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IMT-Mines Ales,Laboratory for Science of Risks,France","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5106387483"],"corresponding_institution_ids":["https://openalex.org/I112991645"],"apc_list":null,"apc_paid":null,"fwci":1.3033,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83072697,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9908000230789185,"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"}},"topics":[{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9908000230789185,"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"}},{"id":"https://openalex.org/T12782","display_name":"Assembly Line Balancing Optimization","score":0.9783999919891357,"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":0.5742893815040588},{"id":"https://openalex.org/keywords/surrogate-model","display_name":"Surrogate model","score":0.5299267172813416},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5036436915397644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45949792861938477},{"id":"https://openalex.org/keywords/manufacturing-engineering","display_name":"Manufacturing engineering","score":0.43836158514022827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28975820541381836},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2510609030723572}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5742893815040588},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.5299267172813416},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5036436915397644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45949792861938477},{"id":"https://openalex.org/C117671659","wikidata":"https://www.wikidata.org/wiki/Q11049265","display_name":"Manufacturing engineering","level":1,"score":0.43836158514022827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28975820541381836},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2510609030723572}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/annsim61499.2024.10732237","is_oa":false,"landing_page_url":"https://doi.org/10.23919/annsim61499.2024.10732237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Annual Modeling and Simulation Conference (ANNSIM)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04769789v1","is_oa":true,"landing_page_url":"https://imt-mines-ales.hal.science/hal-04769789v1/document","pdf_url":"https://imt-mines-ales.hal.science/hal-04769789/document","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://annsim.org/wp-content/uploads/2024/08/ANNSIM2024_164_Paper.pdf","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04769789v1","is_oa":true,"landing_page_url":"https://imt-mines-ales.hal.science/hal-04769789v1/document","pdf_url":"https://imt-mines-ales.hal.science/hal-04769789/document","source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://annsim.org/wp-content/uploads/2024/08/ANNSIM2024_164_Paper.pdf","raw_type":"Conference papers"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403864243.pdf"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W123430343","https://openalex.org/W567610689","https://openalex.org/W2037130454","https://openalex.org/W2093584482","https://openalex.org/W2755087487","https://openalex.org/W2793763890","https://openalex.org/W2887482038","https://openalex.org/W2956371155","https://openalex.org/W3019560754","https://openalex.org/W4254705477","https://openalex.org/W4302406300","https://openalex.org/W4312347226","https://openalex.org/W4367839133","https://openalex.org/W4378446702","https://openalex.org/W6661840906","https://openalex.org/W6678942390","https://openalex.org/W6734758206","https://openalex.org/W6753001681","https://openalex.org/W6768451484","https://openalex.org/W6776681767","https://openalex.org/W6800587020","https://openalex.org/W6838822868","https://openalex.org/W6848190263","https://openalex.org/W6855938718"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W4321369474","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"Airbus":[0,53],"Helicopters":[1,54],"needs":[2,74],"to":[3,10,23,30,39,62,77,101],"modify":[4],"its":[5,68],"manufacturing":[6],"lines":[7],"and":[8,15,29,43,49,81,129],"workshops":[9],"meet":[11],"diverse":[12],"client":[13],"requests":[14],"growing":[16],"demands":[17],"for":[18,67,88],"customization.":[19],"The":[20,35],"challenge":[21],"is":[22,38],"develop":[24],"adaptive,":[25],"dynamic":[26],"production":[27,69],"systems":[28],"optimize":[31],"key":[32],"performance":[33],"indicators.":[34],"main":[36],"goal":[37],"maximize":[40],"customer":[41],"satisfaction":[42],"mini-mize":[44],"delivery":[45],"times,":[46],"investments,":[47],"costs,":[48],"work":[50],"in":[51,112],"progress.":[52],"has":[55,118],"long":[56],"used":[57],"a":[58,83,126],"classical":[59],"simulation-based":[60],"technique":[61],"define":[63],"the":[64,72,89,130],"best":[65],"settings":[66],"lines.":[70],"Nonetheless,":[71],"model":[73,99],"48":[75],"hours":[76],"complete":[78],"each":[79],"run":[80],"test":[82],"single":[84],"set":[85],"of":[86],"parameters":[87],"workshop.":[90],"This":[91],"paper":[92],"presents":[93],"an":[94],"artificial":[95],"intelligence":[96],"based":[97],"surrogate":[98],"designed":[100],"outperform":[102],"traditional":[103],"simulations":[104],"by":[105,125],"potentially":[106],"delivering":[107],"similar":[108],"results":[109],"much":[110],"faster,":[111],"seconds":[113],"rather":[114],"than":[115],"hours.":[116],"It":[117],"been":[119],"trained":[120],"with":[121],"synthetic":[122],"data":[123],"generated":[124],"genetic":[127],"algorithm":[128],"simulation.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}
