{"id":"https://openalex.org/W3014293800","doi":"https://doi.org/10.1080/24725854.2020.1746869","title":"Flexible methods for reliability estimation using aggregate failure-time data","display_name":"Flexible methods for reliability estimation using aggregate failure-time data","publication_year":2020,"publication_date":"2020-03-31","ids":{"openalex":"https://openalex.org/W3014293800","doi":"https://doi.org/10.1080/24725854.2020.1746869","mag":"3014293800"},"language":"en","primary_location":{"id":"doi:10.1080/24725854.2020.1746869","is_oa":false,"landing_page_url":"https://doi.org/10.1080/24725854.2020.1746869","pdf_url":null,"source":{"id":"https://openalex.org/S4210225672","display_name":"IISE Transactions","issn_l":"2472-5854","issn":["2472-5854","2472-5862"],"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":"IISE Transactions","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/A5010326070","display_name":"Samira Karimi","orcid":null},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samira Karimi","raw_affiliation_strings":["Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA;"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA;","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024728249","display_name":"Haitao Liao","orcid":"https://orcid.org/0000-0003-1050-7086"},"institutions":[{"id":"https://openalex.org/I78715868","display_name":"University of Arkansas at Fayetteville","ror":"https://ror.org/05jbt9m15","country_code":"US","type":"education","lineage":["https://openalex.org/I78715868"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haitao Liao","raw_affiliation_strings":["Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA;"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA;","institution_ids":["https://openalex.org/I78715868"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017037570","display_name":"Neng Fan","orcid":"https://orcid.org/0000-0003-4333-3721"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neng Fan","raw_affiliation_strings":["Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5024728249"],"corresponding_institution_ids":["https://openalex.org/I78715868"],"apc_list":null,"apc_paid":null,"fwci":1.2958,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81182824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"53","issue":"1","first_page":"101","last_page":"115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9995999932289124,"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/point-estimation","display_name":"Point estimation","score":0.6465756893157959},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6051700711250305},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5830846428871155},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5650210380554199},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5502731800079346},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5385019183158875},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.47072163224220276},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45659172534942627},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4487919211387634},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.44568175077438354},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4123988747596741},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38808318972587585},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37317955493927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3300822377204895},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.23814073204994202},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11583319306373596}],"concepts":[{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.6465756893157959},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6051700711250305},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5830846428871155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5650210380554199},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5502731800079346},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5385019183158875},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.47072163224220276},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45659172534942627},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4487919211387634},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.44568175077438354},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4123988747596741},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38808318972587585},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37317955493927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3300822377204895},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.23814073204994202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11583319306373596},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/24725854.2020.1746869","is_oa":false,"landing_page_url":"https://doi.org/10.1080/24725854.2020.1746869","pdf_url":null,"source":{"id":"https://openalex.org/S4210225672","display_name":"IISE Transactions","issn_l":"2472-5854","issn":["2472-5854","2472-5862"],"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":"IISE Transactions","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:taf:uiiexx:v:53:y:2021:i:1:p:101-115","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/24725854.2020.1746869","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1570713732","https://openalex.org/W1965784699","https://openalex.org/W1970579875","https://openalex.org/W1971622823","https://openalex.org/W1981100514","https://openalex.org/W1987721624","https://openalex.org/W1992300237","https://openalex.org/W2001421070","https://openalex.org/W2004428145","https://openalex.org/W2009335638","https://openalex.org/W2015777910","https://openalex.org/W2017293177","https://openalex.org/W2020891120","https://openalex.org/W2042836861","https://openalex.org/W2049117165","https://openalex.org/W2052788051","https://openalex.org/W2054533828","https://openalex.org/W2056240720","https://openalex.org/W2061488756","https://openalex.org/W2071236532","https://openalex.org/W2076952689","https://openalex.org/W2089262711","https://openalex.org/W2089790615","https://openalex.org/W2106706098","https://openalex.org/W2122779370","https://openalex.org/W2124812012","https://openalex.org/W2137277132","https://openalex.org/W2138702332","https://openalex.org/W2139699600","https://openalex.org/W2144898279","https://openalex.org/W2147810214","https://openalex.org/W2163214339","https://openalex.org/W2170065761","https://openalex.org/W2170922761","https://openalex.org/W2486894272","https://openalex.org/W2529869754","https://openalex.org/W2551300962","https://openalex.org/W2596425916","https://openalex.org/W2713421705","https://openalex.org/W2734162370","https://openalex.org/W2765703223","https://openalex.org/W2891108772","https://openalex.org/W2915280345","https://openalex.org/W2943440417","https://openalex.org/W2952376399","https://openalex.org/W2966802640","https://openalex.org/W3008574532","https://openalex.org/W4233914278","https://openalex.org/W4237240865","https://openalex.org/W4250735783","https://openalex.org/W4256170606"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W2153238387","https://openalex.org/W4312864369","https://openalex.org/W84255947","https://openalex.org/W2014842417","https://openalex.org/W2502114474","https://openalex.org/W2061347451"],"abstract_inverted_index":{"The":[0],"actual":[1,21],"failure":[2],"times":[3],"of":[4,42,87,97,118,121,190,224],"individual":[5],"components":[6],"are":[7,18,103,137,161,217],"usually":[8],"unavailable":[9],"in":[10,68,94,107,143],"many":[11],"applications.":[12,99],"Instead,":[13],"only":[14,56],"aggregate":[15,70,148],"failure-time":[16,46,71,109,149,232],"data":[17,33],"collected":[19],"by":[20,127],"users,":[22],"due":[23,73],"to":[24,74,182],"technical":[25],"and/or":[26],"economic":[27],"reasons.":[28],"When":[29],"dealing":[30],"with":[31],"such":[32,81],"for":[34,80,139,172,187,198],"reliability":[35,144,214],"estimation,":[36,174],"practitioners":[37],"often":[38],"face":[39],"the":[40,44,49,57,84,129,140,164,176,184,188,193,211,222,230],"challenges":[41],"selecting":[43,225],"underlying":[45,231],"distributions":[47,64,76,89,102,120,136],"and":[48,61,105,157,175,201,220],"corresponding":[50,177],"statistical":[51],"inference":[52],"methods.":[53],"So":[54],"far,":[55],"exponential,":[58],"normal,":[59],"gamma":[60],"inverse":[62],"Gaussian":[63],"have":[65],"been":[66],"used":[67,181],"analyzing":[69],"data,":[72,110],"these":[75],"having":[77],"closed-form":[78],"expressions":[79],"data.":[82,150],"However,":[83],"limited":[85],"choices":[86],"probability":[88,119,227],"cannot":[90],"satisfy":[91],"extensive":[92],"needs":[93],"a":[95,115,158,196,226],"variety":[96],"engineering":[98],"PHase-type":[100],"(PH)":[101],"robust":[104],"flexible":[106,219],"modeling":[108],"as":[111],"they":[112],"can":[113],"mimic":[114],"large":[116],"collection":[117],"non-negative":[122],"random":[123],"variables":[124],"arbitrarily":[125],"closely":[126],"adjusting":[128],"model":[130],"structures.":[131],"In":[132],"this":[133],"article,":[134],"PH":[135],"utilized,":[138],"first":[141],"time,":[142],"estimation":[145,203,215],"based":[146],"on":[147],"A":[151],"Maximum":[152],"Likelihood":[153],"Estimation":[154],"(MLE)":[155],"method":[156],"Bayesian":[159,194],"alternative":[160],"developed.":[162],"For":[163,192],"MLE":[165],"method,":[166,195],"an":[167],"Expectation-Maximization":[168],"algorithm":[169],"is":[170,180,204,234],"developed":[171],"parameter":[173],"Fisher":[178],"information":[179],"construct":[183],"confidence":[185],"intervals":[186],"quantities":[189],"interest.":[191],"procedure":[197],"performing":[199],"point":[200],"interval":[202],"also":[205],"introduced.":[206],"Numerical":[207],"examples":[208],"show":[209],"that":[210],"proposed":[212],"PH-based":[213],"methods":[216],"quite":[218],"alleviate":[221],"burden":[223],"distribution":[228,233],"when":[229],"general":[235],"or":[236],"even":[237],"unknown.":[238]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}