{"id":"https://openalex.org/W4413256761","doi":"https://doi.org/10.1007/s10845-025-02657-7","title":"EBPC: a deep learning cloud computing framework for hybrid stack drilling monitoring","display_name":"EBPC: a deep learning cloud computing framework for hybrid stack drilling monitoring","publication_year":2025,"publication_date":"2025-08-07","ids":{"openalex":"https://openalex.org/W4413256761","doi":"https://doi.org/10.1007/s10845-025-02657-7"},"language":"en","primary_location":{"id":"doi:10.1007/s10845-025-02657-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-025-02657-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-025-02657-7.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10845-025-02657-7.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070684821","display_name":"Jiduo Zhang","orcid":"https://orcid.org/0000-0001-5788-5995"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Jiduo Zhang","raw_affiliation_strings":["Department of Mechanical and Aerospace Engineering, The University of Manchester, Manchester, UK"],"raw_orcid":"https://orcid.org/0000-0001-5788-5995","affiliations":[{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering, The University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116499654","display_name":"Robert Heinemann","orcid":"https://orcid.org/0000-0002-0693-5443"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Robert Heinemann","raw_affiliation_strings":["Department of Mechanical and Aerospace Engineering, The University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering, The University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044650985","display_name":"Otto Jan Bakker","orcid":"https://orcid.org/0000-0002-1862-6955"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Otto Jan Bakker","raw_affiliation_strings":["Department of Mechanical and Aerospace Engineering, The University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering, The University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070684821"],"corresponding_institution_ids":["https://openalex.org/I28407311"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.4643,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6116665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"37","issue":"6","first_page":"2585","last_page":"2609"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","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"}},"topics":[{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","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/T11451","display_name":"Advanced Machining and Optimization Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/cloud-computing","display_name":"Cloud computing","score":0.6607247591018677},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.630673348903656},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6174885034561157},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5251069664955139},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47425997257232666},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.4679127335548401},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.44008946418762207},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.4383803606033325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28330671787261963},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.26760029792785645},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.18445467948913574},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.1112859845161438}],"concepts":[{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6607247591018677},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.630673348903656},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6174885034561157},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5251069664955139},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47425997257232666},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.4679127335548401},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.44008946418762207},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.4383803606033325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28330671787261963},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26760029792785645},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.18445467948913574},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.1112859845161438},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10845-025-02657-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-025-02657-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-025-02657-7.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/bdb48d6e-8db4-440e-82cc-ef5f387d807f","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/bdb48d6e-8db4-440e-82cc-ef5f387d807f","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Zhang, J, Heinemann, R & Bakker, O J 2025, 'EBPC: a deep learning cloud computing framework for hybrid stack drilling monitoring', Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-025-02657-7","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s10845-025-02657-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-025-02657-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-025-02657-7.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G2623053969","display_name":null,"funder_award_id":"201906290245","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413256761.pdf","grobid_xml":"https://content.openalex.org/works/W4413256761.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W788552124","https://openalex.org/W1148858331","https://openalex.org/W1665214252","https://openalex.org/W1964170086","https://openalex.org/W2012651791","https://openalex.org/W2019611862","https://openalex.org/W2079484038","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2117938869","https://openalex.org/W2208965610","https://openalex.org/W2611371469","https://openalex.org/W2784453756","https://openalex.org/W2885195348","https://openalex.org/W3013557734","https://openalex.org/W3033924550","https://openalex.org/W3034778724","https://openalex.org/W3041632065","https://openalex.org/W3087837887","https://openalex.org/W3098189211","https://openalex.org/W3157818305","https://openalex.org/W3161130775","https://openalex.org/W3175356714","https://openalex.org/W3216732410","https://openalex.org/W4205963049","https://openalex.org/W4248245878","https://openalex.org/W4283742768","https://openalex.org/W4385299089","https://openalex.org/W4399322689","https://openalex.org/W4403015895","https://openalex.org/W4403250630","https://openalex.org/W4404641354","https://openalex.org/W4404655147","https://openalex.org/W4405217341","https://openalex.org/W4410363967","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W4413232173","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W2802581102"],"abstract_inverted_index":{"Abstract":[0],"Single-shot":[1],"drilling":[2,24],"of":[3,6,29,76,131,161],"stacks":[4],"composed":[5,130],"Carbon":[7],"Fibre":[8],"Reinforcement":[9],"Polymers":[10],"(CFRP)":[11],"and":[12,64,82,110,139,159],"aluminium":[13],"(AL)":[14],"is":[15,32,91,147,197],"a":[16,56,84,94,122],"common":[17],"operation":[18],"in":[19,50,80,99,112,149,189],"aircraft":[20],"assembly,":[21],"where":[22,194],"adaptive":[23,134],"that":[25],"allows":[26],"real-time":[27],"adjustment":[28],"cutting":[30],"parameters":[31],"crucial":[33],"to":[34,61,171],"improve":[35,42],"assembly":[36],"strength.":[37],"Although":[38],"deep":[39,183],"learning":[40,184],"approaches":[41],"prediction":[43],"accuracy,":[44],"they":[45],"also":[46],"require":[47],"significant":[48],"investment":[49],"computational":[51],"resources.":[52],"This":[53,180],"paper":[54],"introduces":[55],"novel":[57],"cloud":[58,114,127,187],"computing":[59,115,128,166,188],"framework":[60,129,181],"enable":[62],"online":[63,118],"responsive":[65],"process":[66],"incident":[67],"monitoring":[68],"for":[69,88,96,117,186],"CFRP/AL":[70],"drilling.":[71],"By":[72],"measuring":[73],"Signal-to-Noise":[74],"Ratio":[75],"the":[77,89,102,113,157],"harmonic":[78],"components":[79],"thrust":[81],"torque,":[83],"bit":[85,123],"depth":[86,124],"limit":[87],"signals":[90],"established,":[92],"forming":[93],"basis":[95],"data":[97],"minimisation":[98],"line":[100],"with":[101],"signal":[103],"sampling":[104],"boundary":[105],"theory.":[106],"To":[107],"reduce":[108],"congestion":[109],"delay":[111],"system":[116],"tool":[119,190],"condition":[120,191],"monitoring,":[121,192],"optimised":[125],"EBPC":[126],"Exponential":[132],"Backoff":[133],"client":[135],"traffic":[136],"control":[137],"algorithm":[138],"priority":[140],"queue":[141],"based":[142],"Producer-Consumer":[143],"server":[144],"request":[145],"scheduling":[146],"proposed":[148,162],"this":[150],"paper.":[151],"Local":[152],"network":[153],"stress":[154],"tests":[155],"confirms":[156],"efficiency":[158],"resilience":[160],"framework,":[163],"while":[164],"remote":[165],"experiments":[167],"demonstrate":[168],"its":[169],"capability":[170],"operate":[172],"effectively":[173],"across":[174],"all":[175],"Europe":[176],"through":[177],"different":[178],"connectivities.":[179],"advances":[182],"applications":[185],"especially":[193],"low-latency":[195],"response":[196],"essential.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
