{"id":"https://openalex.org/W34339474","doi":"https://doi.org/10.1080/00224065.2009.11917791","title":"Statistical Adjustments to Engineering Models","display_name":"Statistical Adjustments to Engineering Models","publication_year":2009,"publication_date":"2009-10-01","ids":{"openalex":"https://openalex.org/W34339474","doi":"https://doi.org/10.1080/00224065.2009.11917791","mag":"34339474"},"language":"en","primary_location":{"id":"doi:10.1080/00224065.2009.11917791","doi":"https://doi.org/10.1080/00224065.2009.11917791","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00224065.2009.11917791","pdf_url":null,"source":{"id":"https://openalex.org/S166831694","display_name":"Journal of Quality Technology","issn_l":"0022-4065","issn":["0022-4065","2575-6230"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","fnege-3","jufo-1","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Quality Technology","raw_type":"journal-article"},"volume":null,"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/A5015629734","display_name":"V. Roshan Joseph","orcid":"https://orcid.org/0000-0002-9430-5301","observed_orcids":["https://orcid.org/0000-0002-9430-5301"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"V. Roshan Joseph","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA 30332"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA 30332","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075529785","display_name":"Shreyes N. Melkote","orcid":"https://orcid.org/0000-0003-3816-0002","observed_orcids":["https://orcid.org/0000-0003-3816-0002"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shreyes N. Melkote","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA 30332"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA 30332","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":5.4201,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":{"value":0.94988058,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"41","issue":"4","first_page":"362","last_page":"375"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.003800000064074993,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/model-modification","display_name":"model modification","score":0.6690000295639038},{"id":"https://openalex.org/keywords/empirical-bayes","display_name":"empirical Bayes","score":0.878000020980835},{"id":"https://openalex.org/keywords/sequential-adjustment","display_name":"sequential adjustment","score":0.6190000176429749},{"id":"https://openalex.org/keywords/quality-improvement","display_name":"quality improvement","score":0.5289999842643738},{"id":"https://openalex.org/keywords/surface-roughness-prediction","display_name":"surface roughness prediction","score":0.765999972820282},{"id":"https://openalex.org/keywords/microcuttings","display_name":"microcuttings","score":0.9440000057220459}],"concepts":[{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.751724123954773},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.6110753417015076},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5996863842010498},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5315760374069214},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.4149817228317261},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3554639220237732},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3227561116218567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3016962707042694},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.28571343421936035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23579201102256775},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21279031038284302},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20553097128868103},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1999334692955017},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/00224065.2009.11917791","doi":"https://doi.org/10.1080/00224065.2009.11917791","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00224065.2009.11917791","pdf_url":null,"source":{"id":"https://openalex.org/S166831694","display_name":"Journal of Quality Technology","issn_l":"0022-4065","issn":["0022-4065","2575-6230"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","dongbi-b","fnege-3","jufo-1","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Quality Technology","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.215.6548","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.215.6548","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www2.isye.gatech.edu/statistics/papers/08-02.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W236410074","https://openalex.org/W651150315","https://openalex.org/W1499018153","https://openalex.org/W1553296127","https://openalex.org/W1967132311","https://openalex.org/W1970349560","https://openalex.org/W1973333099","https://openalex.org/W1974063953","https://openalex.org/W1978738742","https://openalex.org/W1991413021","https://openalex.org/W2002251485","https://openalex.org/W2002371494","https://openalex.org/W2018044188","https://openalex.org/W2027319489","https://openalex.org/W2063978378","https://openalex.org/W2070094080","https://openalex.org/W2073401015","https://openalex.org/W2092612581","https://openalex.org/W2098043077","https://openalex.org/W2135046866","https://openalex.org/W2143991987","https://openalex.org/W2585172680","https://openalex.org/W3146425672","https://openalex.org/W4244393914","https://openalex.org/W4249753629","https://openalex.org/W4291114417"],"related_works":["https://openalex.org/W2166552921","https://openalex.org/W776312405","https://openalex.org/W2792564823","https://openalex.org/W3005762059","https://openalex.org/W2571629970","https://openalex.org/W2074199287","https://openalex.org/W1989634353","https://openalex.org/W760887449","https://openalex.org/W2117079164","https://openalex.org/W2079435060"],"abstract_inverted_index":{"Statistical":[0],"models":[1,10,30,50,57],"are":[2,17,78,85,100],"commonly":[3],"used":[4],"in":[5,80,120],"quality-improvement":[6],"studies.":[7],"However,":[8],"such":[9],"tend":[11],"to":[12,69,104],"perform":[13],"poorly":[14],"when":[15],"predictions":[16],"made":[18],"away":[19],"from":[20],"the":[21,26,33,37,53,70,109,125],"observed":[22],"data":[23],"points.":[24],"On":[25],"other":[27],"hand,":[28],"engineering":[29,56,71],"derived":[31],"using":[32,73,113],"underlying":[34],"physics":[35],"of":[36,55,108,116,127],"process":[38,123],"do":[39],"not":[40],"always":[41],"match":[42],"satisfactorily":[43],"with":[44],"reality.":[45],"This":[46],"article":[47],"proposes":[48],"engineering\u2014statistical":[49,62],"that":[51,99],"overcome":[52],"disadvantages":[54],"and":[58,84,124],"statistical":[59],"models.":[60],"The":[61,76,106],"model":[63,72],"is":[64,111],"obtained":[65],"through":[66],"some":[67],"adjustments":[68,77,98],"experimental":[74],"data.":[75],"done":[79],"a":[81,114,121,128],"sequential":[82],"way":[83],"based":[86],"on":[87],"empirical":[88],"Bayes":[89],"methods.":[90],"We":[91],"also":[92],"develop":[93],"approximate":[94],"frequentist":[95],"procedures":[96],"for":[97],"computationally":[101],"much":[102],"easier":[103],"implement.":[105],"usefulness":[107],"methodology":[110],"illustrated":[112],"problem":[115],"predicting":[117],"surface":[118],"roughness":[119],"microcutting":[122],"optimization":[126],"spot-welding":[129],"process.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":3}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-06-24T00:00:00"}
