{"id":"https://openalex.org/W3035673799","doi":"https://doi.org/10.1109/tai.2021.3065011","title":"Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach","display_name":"Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach","publication_year":2021,"publication_date":"2021-04-01","ids":{"openalex":"https://openalex.org/W3035673799","doi":"https://doi.org/10.1109/tai.2021.3065011","mag":"3035673799"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2021.3065011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2021.3065011","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2006.08828","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ayman Moawad","orcid":"https://orcid.org/0000-0001-6658-9012"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ayman Moawad","raw_affiliation_strings":["Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA"],"raw_orcid":"https://orcid.org/0000-0001-6658-9012","affiliations":[{"raw_affiliation_string":"Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA","institution_ids":["https://openalex.org/I1282105669"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ehsan Islam","orcid":"https://orcid.org/0000-0002-0022-0180"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ehsan Islam","raw_affiliation_strings":["Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA"],"raw_orcid":"https://orcid.org/0000-0002-0022-0180","affiliations":[{"raw_affiliation_string":"Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA","institution_ids":["https://openalex.org/I1282105669"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Namdoo Kim","orcid":"https://orcid.org/0000-0002-5201-539X"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Namdoo Kim","raw_affiliation_strings":["Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA"],"raw_orcid":"https://orcid.org/0000-0002-5201-539X","affiliations":[{"raw_affiliation_string":"Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA","institution_ids":["https://openalex.org/I1282105669"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ram Vijayagopal","orcid":"https://orcid.org/0000-0003-2001-3055"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ram Vijayagopal","raw_affiliation_strings":["Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA"],"raw_orcid":"https://orcid.org/0000-0003-2001-3055","affiliations":[{"raw_affiliation_string":"Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA","institution_ids":["https://openalex.org/I1282105669"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Aymeric Rousseau","orcid":"https://orcid.org/0000-0002-4023-9951"},"institutions":[{"id":"https://openalex.org/I1282105669","display_name":"Argonne National Laboratory","ror":"https://ror.org/05gvnxz63","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282105669","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aymeric Rousseau","raw_affiliation_strings":["Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA"],"raw_orcid":"https://orcid.org/0000-0002-4023-9951","affiliations":[{"raw_affiliation_string":"Vehicle and Mobility Simulation Group, Argonne National Laboratory, Lemont, IL, USA","institution_ids":["https://openalex.org/I1282105669"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wei Biao Wu","orcid":"https://orcid.org/0000-0003-4310-9965"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Biao Wu","raw_affiliation_strings":["Department of Statistics, The University of Chicago, Chicago, IL, USA"],"raw_orcid":"https://orcid.org/0000-0003-4310-9965","affiliations":[{"raw_affiliation_string":"Department of Statistics, The University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4022,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.48578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2","issue":"2","first_page":"185","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.37209999561309814,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12617","display_name":"Energy, Environment, and Transportation Policies","score":0.37209999561309814,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.06499999761581421,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.03629999980330467,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.7175999879837036},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.6790000200271606},{"id":"https://openalex.org/keywords/multiplier","display_name":"Multiplier (economics)","score":0.3801000118255615},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.3422999978065491},{"id":"https://openalex.org/keywords/cost-estimate","display_name":"Cost estimate","score":0.3197999894618988}],"concepts":[{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.7175999879837036},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6790000200271606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5562999844551086},{"id":"https://openalex.org/C124584101","wikidata":"https://www.wikidata.org/wiki/Q1053266","display_name":"Multiplier (economics)","level":2,"score":0.3801000118255615},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33959999680519104},{"id":"https://openalex.org/C93983250","wikidata":"https://www.wikidata.org/wiki/Q795053","display_name":"Cost estimate","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3181999921798706},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2921999990940094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2809000015258789},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27459999918937683},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.2680000066757202},{"id":"https://openalex.org/C95821633","wikidata":"https://www.wikidata.org/wiki/Q973302","display_name":"Cost driver","level":2,"score":0.25760000944137573}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tai.2021.3065011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2021.3065011","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2006.08828","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.08828","pdf_url":"https://arxiv.org/pdf/2006.08828","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:osti.gov:1837219","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/1837219","pdf_url":"https://www.osti.gov/servlets/purl/1837219","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2006.08828","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.08828","pdf_url":"https://arxiv.org/pdf/2006.08828","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1032884540","display_name":null,"funder_award_id":"DE-AC02\u201306CH11357","funder_id":"https://openalex.org/F4320310910","funder_display_name":"Savannah River Operations Office, U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320310910","display_name":"Savannah River Operations Office, U.S. Department of Energy","ror":"https://ror.org/05hhm9a98"},{"id":"https://openalex.org/F4320332360","display_name":"Office of Energy Efficiency and Renewable Energy","ror":"https://ror.org/02xznz413"},{"id":"https://openalex.org/F4320337713","display_name":"Vehicle Technologies Office","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1481763865","https://openalex.org/W1502810280","https://openalex.org/W1678356000","https://openalex.org/W1875842236","https://openalex.org/W1990836268","https://openalex.org/W2024046085","https://openalex.org/W2059958079","https://openalex.org/W2070493638","https://openalex.org/W2102099143","https://openalex.org/W2125847307","https://openalex.org/W2295598076","https://openalex.org/W2468696781","https://openalex.org/W2487898712","https://openalex.org/W2745244103","https://openalex.org/W2999615587","https://openalex.org/W4235334589","https://openalex.org/W6601738913","https://openalex.org/W6608293291","https://openalex.org/W6617488683","https://openalex.org/W6633488972","https://openalex.org/W6682658890","https://openalex.org/W6727366246","https://openalex.org/W6745609711","https://openalex.org/W6748281036","https://openalex.org/W6750729320","https://openalex.org/W6755712434","https://openalex.org/W6760717196","https://openalex.org/W6766846328","https://openalex.org/W6766985858","https://openalex.org/W6769692591","https://openalex.org/W6884950754"],"related_works":[],"abstract_inverted_index":{"The":[0,221],"broader":[1],"ambition":[2],"of":[3,15,18,38,73,110,155,189,204,211,243],"this":[4,39],"article":[5],"is":[6,182],"to":[7,22,60,85,120,129,139,145,239],"popularize":[8],"an":[9,83],"approach":[10,59],"for":[11,27,49,92],"the":[12,16,36,99,108,118,127,156,159,187],"fair":[13],"distribution":[14],"quantity":[17],"a":[19,42,50,57,71,166,226],"system's":[20],"output":[21],"its":[23,65],"subsystems":[24],"while":[25],"allowing":[26],"underlying":[28],"complex":[29],"subsystem":[30],"level":[31,105],"interactions.":[32],"Particularly,":[33],"we":[34],"present":[35,194],"use":[37],"framework":[40],"on":[41,225],"very":[43],"specific":[44],"(but":[45],"generalizable)":[46],"application,":[47],"interesting":[48],"more":[51],"general":[52],"AI":[53],"audience.":[54],"We":[55,81],"detail":[56],"data-driven":[58],"vehicle":[61,95,176,244],"price":[62,67,96,103,132,188],"modeling":[63],"and":[64,78,89,94,123,126,191,209,213],"component":[66,93,206],"estimation":[68,97],"by":[69,229],"leveraging":[70],"combination":[72],"concepts":[74],"from":[75],"machine":[76],"learning":[77],"game":[79],"theory.":[80],"show":[82],"alternative":[84],"common":[86],"teardown":[87,116],"methodologies":[88],"surveying":[90],"approaches":[91],"at":[98,158],"manufacturer's":[100],"suggested":[101],"retail":[102,131],"(MSRP)":[104],"that":[106,201],"has":[107],"advantage":[109],"bypassing":[111],"uncertainties":[112],"involved":[113],"in":[114,171,195],"gathering":[115],"data,":[117],"need":[119,128],"perform":[121,130],"expensive":[122],"biased":[124],"surveying,":[125],"equivalent":[133],"or":[134],"indirect":[135],"cost":[136],"multiplier":[137],"adjustments":[138],"mark":[140],"up":[141],"direct":[142],"manufacturing":[143],"costs":[144],"MSRP.":[146],"This":[147],"novel":[148],"exercise":[149],"not":[150],"only":[151],"provides":[152],"accurate":[153],"pricing":[154,172],"technologies":[157,190],"customer":[160],"level,":[161],"but":[162],"also":[163,183],"shows":[164],"the,":[165],"priori":[167],"known,":[168],"large":[169],"gaps":[170],"strategies":[173],"between":[174,186],"manufacturers,":[175],"classes,":[177],"market":[178],"segments,":[179],"etc.":[180],"There":[181],"clear":[184],"interaction":[185],"other":[192],"specifications":[193],"vehicles.":[196],"Those":[197],"results":[198],"are":[199,223],"indication":[200],"old":[202],"methods":[203],"manufacturer-level":[205],"costing,":[207],"aggregation,":[208],"application":[210],"flat":[212],"rigid":[214],"adjustment":[215],"factors":[216],"should":[217],"be":[218],"carefully":[219],"examined.":[220],"findings":[222],"based":[224],"database":[227],"developed":[228],"Argonne,":[230],"which":[231],"includes":[232],"over":[233],"64":[234],"000":[235],"vehicles":[236],"covering":[237],"MY1990":[238],"MY2020":[240],"with":[241],"hundreds":[242],"specs.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2020-06-19T00:00:00"}
