{"id":"https://openalex.org/W4400894619","doi":"https://doi.org/10.1080/00207543.2024.2378907","title":"A dual-critic DQN architecture for lifter assignment in multi-floor semiconductor FAB","display_name":"A dual-critic DQN architecture for lifter assignment in multi-floor semiconductor FAB","publication_year":2024,"publication_date":"2024-07-22","ids":{"openalex":"https://openalex.org/W4400894619","doi":"https://doi.org/10.1080/00207543.2024.2378907"},"language":"en","primary_location":{"id":"doi:10.1080/00207543.2024.2378907","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2024.2378907","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"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 Production Research","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/A5077846932","display_name":"Jiwon Kim","orcid":"https://orcid.org/0000-0002-5182-2667"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jiwon Kim","raw_affiliation_strings":["Yonsei University","Department of Industrial Engineering, Yonsei University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Department of Industrial Engineering, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005103838","display_name":"Jeonghoon Mo","orcid":"https://orcid.org/0000-0001-5151-6486"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jeonghoon Mo","raw_affiliation_strings":["Yonsei University","Department of Industrial Engineering, Yonsei University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Department of Industrial Engineering, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005103838"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":0.3637,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.647713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"63","issue":"4","first_page":"1450","last_page":"1472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.8838000297546387,"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"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.8838000297546387,"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"}},{"id":"https://openalex.org/T10468","display_name":"Photovoltaic System Optimization Techniques","score":0.8833000063896179,"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/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.8826000094413757,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/dual","display_name":"Dual (grammatical number)","score":0.7572401165962219},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6445164084434509},{"id":"https://openalex.org/keywords/semiconductor-device-fabrication","display_name":"Semiconductor device fabrication","score":0.5804985761642456},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47333627939224243},{"id":"https://openalex.org/keywords/semiconductor","display_name":"Semiconductor","score":0.4609663188457489},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.3835003972053528},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.36105650663375854},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.13764506578445435}],"concepts":[{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.7572401165962219},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6445164084434509},{"id":"https://openalex.org/C66018809","wikidata":"https://www.wikidata.org/wiki/Q1570432","display_name":"Semiconductor device fabrication","level":3,"score":0.5804985761642456},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47333627939224243},{"id":"https://openalex.org/C108225325","wikidata":"https://www.wikidata.org/wiki/Q11456","display_name":"Semiconductor","level":2,"score":0.4609663188457489},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.3835003972053528},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36105650663375854},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.13764506578445435},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/00207543.2024.2378907","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207543.2024.2378907","pdf_url":null,"source":{"id":"https://openalex.org/S65690446","display_name":"International Journal of Production Research","issn_l":"0020-7543","issn":["0020-7543","1366-588X"],"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 Production Research","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:taf:tprsxx:v:63:y:2025:i:4:p:1450-1472","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/00207543.2024.2378907","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G580843394","display_name":null,"funder_award_id":"2023-11-0329","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1757796397","https://openalex.org/W1949003493","https://openalex.org/W1983350566","https://openalex.org/W2086675367","https://openalex.org/W2145339207","https://openalex.org/W2173564293","https://openalex.org/W2194775991","https://openalex.org/W2224541676","https://openalex.org/W2811338889","https://openalex.org/W2997873913","https://openalex.org/W3034786558","https://openalex.org/W3049468855","https://openalex.org/W3154178432","https://openalex.org/W4205112278","https://openalex.org/W4226263181","https://openalex.org/W4386412292"],"related_works":["https://openalex.org/W2317351040","https://openalex.org/W4285447065","https://openalex.org/W2588198209","https://openalex.org/W2952466936","https://openalex.org/W1909006023","https://openalex.org/W3200723557","https://openalex.org/W4205824991","https://openalex.org/W1988622314","https://openalex.org/W2393949104","https://openalex.org/W3046201198"],"abstract_inverted_index":{"This":[0,91],"paper":[1],"proposes":[2],"a":[3,37,80],"deep":[4],"reinforcement":[5],"learning-based":[6],"lifter":[7],"assignment":[8],"algorithm":[9,133],"utilising":[10],"Deep":[11],"Q-network":[12],"(DQN)":[13],"to":[14,86],"minimise":[15],"the":[16,25,52,59,74,111,114,131],"total":[17],"inter-floor":[18],"delivery":[19,34,61],"time":[20],"in":[21,30,43],"semiconductor":[22],"manufacturing.":[23],"Given":[24],"complexities":[26],"and":[27,50],"randomness":[28],"inherent":[29],"manufacturing":[31],"environments,":[32],"predicting":[33,69],"times":[35],"poses":[36],"significant":[38],"challenge":[39,49],"for":[40],"companies":[41],"operating":[42],"such":[44],"domains.":[45],"To":[46],"address":[47],"this":[48],"improve":[51],"accuracy":[53,95],"of":[54,63,113],"delay":[55],"prediction,":[56],"we":[57],"partition":[58],"end-to-end":[60,76],"process":[62],"individual":[64],"lot":[65],"systematically,":[66],"focusing":[67],"on":[68],"segment":[70],"delays":[71],"rather":[72],"than":[73],"overall":[75],"delay.":[77],"We":[78,122],"introduce":[79],"unique":[81],"dual":[82],"critic":[83],"architecture":[84],"designed":[85],"handle":[87],"these":[88],"segmented":[89],"steps.":[90],"innovative":[92],"approach":[93],"enhances":[94],"by":[96],"capturing":[97],"nuanced":[98],"information":[99],"at":[100],"each":[101],"step,":[102],"which":[103],"is":[104],"stored":[105],"as":[106],"trajectories.":[107],"Simulation":[108],"results":[109],"substantiate":[110],"effectiveness":[112],"proposed":[115,132],"architecture,":[116],"comparing":[117],"favorably":[118],"against":[119],"existing":[120],"algorithms.":[121,136],"conduct":[123],"comparative":[124],"analyses":[125],"with":[126],"benchmark":[127],"algorithms,":[128],"revealing":[129],"that":[130],"outperforms":[134],"other":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
