{"id":"https://openalex.org/W2904780227","doi":"https://doi.org/10.1109/coase.2018.8560567","title":"Data Fusion Pipelines for Autonomous Smart Manufacturing","display_name":"Data Fusion Pipelines for Autonomous Smart Manufacturing","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2904780227","doi":"https://doi.org/10.1109/coase.2018.8560567","mag":"2904780227"},"language":"en","primary_location":{"id":"doi:10.1109/coase.2018.8560567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2018.8560567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","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/A5100386486","display_name":"Xiaoyu Chen","orcid":"https://orcid.org/0000-0002-1870-5290"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaoyu Chen","raw_affiliation_strings":["Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085868833","display_name":"Ran Jin","orcid":"https://orcid.org/0000-0003-3847-4538"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ran Jin","raw_affiliation_strings":["Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100386486"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":1.762,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8810159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1203","last_page":"1208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.983299970626831,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.983299970626831,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9502999782562256,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9083999991416931,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.7413036227226257},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6313290596008301},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6066268086433411},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5126251578330994},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4499826431274414},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3824542760848999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3618178367614746},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34950584173202515},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.3417459726333618},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22539815306663513},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.16830676794052124},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15375912189483643},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.09751957654953003}],"concepts":[{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.7413036227226257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6313290596008301},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6066268086433411},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5126251578330994},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4499826431274414},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3824542760848999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3618178367614746},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34950584173202515},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3417459726333618},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22539815306663513},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.16830676794052124},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15375912189483643},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.09751957654953003}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coase.2018.8560567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2018.8560567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1022778776","https://openalex.org/W1907420209","https://openalex.org/W1966836595","https://openalex.org/W1969233101","https://openalex.org/W2016508327","https://openalex.org/W2038817616","https://openalex.org/W2057579372","https://openalex.org/W2068161803","https://openalex.org/W2089468765","https://openalex.org/W2135046866","https://openalex.org/W2149427297","https://openalex.org/W2154983631","https://openalex.org/W2162876875","https://openalex.org/W2163286960","https://openalex.org/W2169707043","https://openalex.org/W2322663024","https://openalex.org/W2547386789","https://openalex.org/W2566168132","https://openalex.org/W2584792247","https://openalex.org/W2610350439","https://openalex.org/W2621700966","https://openalex.org/W2623144283","https://openalex.org/W2765833492","https://openalex.org/W2767448576","https://openalex.org/W2810240646","https://openalex.org/W4214717370","https://openalex.org/W4245798716"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W1995889332","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385"],"abstract_inverted_index":{"In":[0],"smart":[1,35],"manufacturing,":[2,40],"data-driven":[3,19],"models":[4,20],"characterize":[5],"variable":[6],"relationships,":[7],"which":[8],"are":[9,28,132],"used":[10,133],"for":[11,59,149],"decision":[12],"making":[13],"to":[14,37,76,134],"achieve":[15],"optimal":[16],"operations.":[17],"However,":[18],"may":[21],"not":[22],"be":[23],"adequate":[24],"when":[25],"modeling":[26,130],"assumptions":[27],"violated":[29],"in":[30,111,120],"manufacturing":[31,36,60,131,157],"personalization.":[32],"To":[33,63],"advance":[34],"future":[38],"autonomous":[39],"we":[41,68],"propose":[42],"data":[43,53,99,115],"fusion":[44,54,100,116],"pipelines":[45,71,79],"as":[46],"a":[47,73,150],"combination":[48],"of":[49,97,113,140,153],"method":[50,75,154],"options":[51],"(i.e.,":[52],"or":[55],"machine":[56,102],"learning":[57,103],"steps)":[58],"process":[61],"modeling.":[62],"avoid":[64],"executing":[65,112],"all":[66,114],"pipelines,":[67],"associate":[69],"the":[70,78,89,95,136,141],"with":[72,80],"learning-to-rank":[74],"rank":[77],"Top-N":[81],"prediction":[82],"accuracy,":[83],"where":[84],"N":[85],"is":[86,147],"determined":[87],"by":[88],"computation":[90,109,161],"resources.":[91],"This":[92],"approach":[93,146],"improves":[94],"ease":[96],"using":[98],"and":[101,105,127,138,159,163],"methods,":[104],"effectively":[106],"avoids":[107],"large":[108],"workloads":[110],"pipelines.":[117],"Case":[118],"studies":[119],"thermal":[121],"spray":[122],"coating,":[123],"aerosol\u00ae":[124],"jet":[125],"printing,":[126],"fused":[128],"deposition":[129],"demonstrate":[135],"effectiveness":[137],"efficiency":[139],"proposed":[142,145],"approach.":[143],"The":[144],"scalable":[148],"larger":[151],"collection":[152],"options,":[155],"different":[156],"conditions,":[158],"various":[160],"systems":[162],"networks.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}