{"id":"https://openalex.org/W298105042","doi":"https://doi.org/10.1198/004017008000000118","title":"Estimation of Process Parameters to Determine the Optimum Diagnosis Interval for Control of Defective Items","display_name":"Estimation of Process Parameters to Determine the Optimum Diagnosis Interval for Control of Defective Items","publication_year":2008,"publication_date":"2008-05-01","ids":{"openalex":"https://openalex.org/W298105042","doi":"https://doi.org/10.1198/004017008000000118","mag":"298105042"},"language":"en","primary_location":{"id":"doi:10.1198/004017008000000118","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017008000000118","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","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/A5029852186","display_name":"Tirthankar Dasgupta","orcid":"https://orcid.org/0000-0001-6590-6936"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tirthankar Dasgupta","raw_affiliation_strings":["Department of Statistics Harvard University Cambridge, MA 02138"],"affiliations":[{"raw_affiliation_string":"Department of Statistics Harvard University Cambridge, MA 02138","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084419948","display_name":"Abhyuday Mandal","orcid":"https://orcid.org/0000-0001-9461-1483"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhyuday Mandal","raw_affiliation_strings":["Department of Statistics University of Georgia Athens, GA 30602"],"affiliations":[{"raw_affiliation_string":"Department of Statistics University of Georgia Athens, GA 30602","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029852186"],"corresponding_institution_ids":["https://openalex.org/I2801851002"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02397759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"2","first_page":"167","last_page":"181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9972000122070312,"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"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9972000122070312,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9907000064849854,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.9797999858856201,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/taguchi-methods","display_name":"Taguchi methods","score":0.7543247938156128},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.6461915969848633},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6394856572151184},{"id":"https://openalex.org/keywords/credible-interval","display_name":"Credible interval","score":0.5280535817146301},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5054900646209717},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4777480959892273},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4693520963191986},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.46760669350624084},{"id":"https://openalex.org/keywords/interval-estimation","display_name":"Interval estimation","score":0.43725529313087463},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4091099202632904},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.39582550525665283},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.34851735830307007},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3252995014190674},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.28446710109710693},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27304500341415405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23151394724845886},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20101603865623474},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.18407335877418518}],"concepts":[{"id":"https://openalex.org/C83469408","wikidata":"https://www.wikidata.org/wiki/Q2036525","display_name":"Taguchi methods","level":2,"score":0.7543247938156128},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6461915969848633},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6394856572151184},{"id":"https://openalex.org/C121117317","wikidata":"https://www.wikidata.org/wiki/Q4439221","display_name":"Credible interval","level":3,"score":0.5280535817146301},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5054900646209717},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4777480959892273},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4693520963191986},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.46760669350624084},{"id":"https://openalex.org/C205167067","wikidata":"https://www.wikidata.org/wiki/Q3300636","display_name":"Interval estimation","level":3,"score":0.43725529313087463},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4091099202632904},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.39582550525665283},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.34851735830307007},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3252995014190674},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.28446710109710693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27304500341415405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23151394724845886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20101603865623474},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.18407335877418518},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1198/004017008000000118","is_oa":false,"landing_page_url":"https://doi.org/10.1198/004017008000000118","pdf_url":null,"source":{"id":"https://openalex.org/S985303","display_name":"Technometrics","issn_l":"0040-1706","issn":["0040-1706","1537-2723"],"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":"Technometrics","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.590.8984","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.590.8984","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.stat.harvard.edu/Faculty_Content/dasgupta/DasguptaMandal.pdf","raw_type":"text"},{"id":"mag:298105042","is_oa":false,"landing_page_url":"https://dialnet.unirioja.es/servlet/articulo?codigo=4617437","pdf_url":null,"source":{"id":"https://openalex.org/S13624874","display_name":"Quality Engineering","issn_l":"0898-2112","issn":["0898-2112","1532-4222"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":"Quality Engineering","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1976278338","https://openalex.org/W1978762042","https://openalex.org/W1980223015","https://openalex.org/W1980904400","https://openalex.org/W1982187072","https://openalex.org/W1986291222","https://openalex.org/W2018653487","https://openalex.org/W2031597096","https://openalex.org/W2064737834","https://openalex.org/W2075016529","https://openalex.org/W2091951637","https://openalex.org/W2105740884","https://openalex.org/W2146720487","https://openalex.org/W2156184993","https://openalex.org/W2515726670","https://openalex.org/W4238889147","https://openalex.org/W4251861477"],"related_works":["https://openalex.org/W2008432355","https://openalex.org/W2007091762","https://openalex.org/W2013383904","https://openalex.org/W2292163971","https://openalex.org/W1988842586","https://openalex.org/W2368340708","https://openalex.org/W2136918375","https://openalex.org/W2004822919","https://openalex.org/W2885414003","https://openalex.org/W2495456385","https://openalex.org/W3017290846","https://openalex.org/W2085667230","https://openalex.org/W2118490038","https://openalex.org/W622736006","https://openalex.org/W3041840251","https://openalex.org/W2065775592","https://openalex.org/W2117968786","https://openalex.org/W133113886","https://openalex.org/W3174733655","https://openalex.org/W1829797611"],"abstract_inverted_index":{"The":[0],"online":[1],"quality":[2],"monitoring":[3],"procedure":[4],"for":[5,99],"attributes":[6],"proposed":[7,108],"by":[8,16],"Taguchi":[9],"has":[10],"been":[11],"critically":[12],"studied":[13],"and":[14,52,78,102,113],"extended":[15],"a":[17,59,87,114,118],"few":[18],"researchers.":[19],"Determination":[20],"of":[21,28,39,48,106],"the":[22,33,49,64,75,83,97,100,104,107],"optimum":[23],"diagnosis":[24,50],"interval":[25,51],"requires":[26],"estimation":[27],"some":[29],"parameters":[30,41,66],"related":[31],"to":[32,44,62,90],"process":[34,65,70],"failure":[35],"mechanism.":[36],"Improper":[37],"estimates":[38],"these":[40],"may":[42],"lead":[43],"an":[45],"incorrect":[46],"choice":[47],"thus":[53],"huge":[54],"economic":[55],"penalties.":[56],"We":[57,85],"propose":[58],"Bayesian":[60],"approach":[61],"estimate":[63],"under":[67],"two":[68],"different":[69],"models,":[71],"commonly":[72],"called":[73],"as":[74],"case":[76,79,115],"II":[77],"III":[80],"models":[81],"in":[82,95],"literature.":[84],"discuss":[86],"systematic":[88],"way":[89],"use":[91],"available":[92],"engineering":[93],"knowledge":[94],"eliciting":[96],"prior":[98],"parameters,":[101],"demonstrate":[103],"performance":[105],"method":[109],"using":[110],"extensive":[111],"simulation":[112],"study":[116],"from":[117],"hot":[119],"rolling":[120],"mill.":[121]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}