{"id":"https://openalex.org/W1975629958","doi":"https://doi.org/10.1109/cisim.2010.5643668","title":"Evaluating the statistical process control performance for monitoring stationary observations using Monte Carlo simulation","display_name":"Evaluating the statistical process control performance for monitoring stationary observations using Monte Carlo simulation","publication_year":2010,"publication_date":"2010-10-01","ids":{"openalex":"https://openalex.org/W1975629958","doi":"https://doi.org/10.1109/cisim.2010.5643668","mag":"1975629958"},"language":"en","primary_location":{"id":"doi:10.1109/cisim.2010.5643668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisim.2010.5643668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM)","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/A5051173266","display_name":"Karin Kandananond","orcid":"https://orcid.org/0000-0001-7993-5375"},"institutions":[{"id":"https://openalex.org/I4210132654","display_name":"Valaya Alongkorn Rajabhat University","ror":"https://ror.org/04hp7kk26","country_code":"TH","type":"education","lineage":["https://openalex.org/I4210132654"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Karin Kandananond","raw_affiliation_strings":["Rajabhat University Valaya-Alongkorn, Klong Luang, Pathum Thani, Thailand","Rajabhat University Valaya-Alongkorn, 1 Moo 20 km 48, Klong-Luang Dist., Prathumthani, Thailand"],"affiliations":[{"raw_affiliation_string":"Rajabhat University Valaya-Alongkorn, Klong Luang, Pathum Thani, Thailand","institution_ids":["https://openalex.org/I4210132654"]},{"raw_affiliation_string":"Rajabhat University Valaya-Alongkorn, 1 Moo 20 km 48, Klong-Luang Dist., Prathumthani, Thailand","institution_ids":["https://openalex.org/I4210132654"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5051173266"],"corresponding_institution_ids":["https://openalex.org/I4210132654"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09217426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":null,"first_page":"182","last_page":"186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9997000098228455,"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":0.9997000098228455,"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/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.9894999861717224,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9847000241279602,"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/ewma-chart","display_name":"EWMA chart","score":0.8835737109184265},{"id":"https://openalex.org/keywords/control-chart","display_name":"Control chart","score":0.8639049530029297},{"id":"https://openalex.org/keywords/statistical-process-control","display_name":"Statistical process control","score":0.7088797688484192},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.638197124004364},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.6366304755210876},{"id":"https://openalex.org/keywords/moving-average","display_name":"Moving average","score":0.5984338521957397},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5742268562316895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5715277194976807},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5259592533111572},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5127452611923218},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31091606616973877}],"concepts":[{"id":"https://openalex.org/C74746147","wikidata":"https://www.wikidata.org/wiki/Q5324652","display_name":"EWMA chart","level":4,"score":0.8835737109184265},{"id":"https://openalex.org/C196985124","wikidata":"https://www.wikidata.org/wiki/Q1369242","display_name":"Control chart","level":3,"score":0.8639049530029297},{"id":"https://openalex.org/C113644684","wikidata":"https://www.wikidata.org/wiki/Q1356717","display_name":"Statistical process control","level":3,"score":0.7088797688484192},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.638197124004364},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.6366304755210876},{"id":"https://openalex.org/C175706884","wikidata":"https://www.wikidata.org/wiki/Q1130194","display_name":"Moving average","level":2,"score":0.5984338521957397},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5742268562316895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5715277194976807},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5259592533111572},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5127452611923218},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31091606616973877},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisim.2010.5643668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisim.2010.5643668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM)","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":14,"referenced_works":["https://openalex.org/W131998157","https://openalex.org/W988335224","https://openalex.org/W1489457921","https://openalex.org/W1988300964","https://openalex.org/W2030236106","https://openalex.org/W2077383827","https://openalex.org/W2313953460","https://openalex.org/W2789525605","https://openalex.org/W3015379812","https://openalex.org/W4211169888","https://openalex.org/W4250374447","https://openalex.org/W4285719527","https://openalex.org/W6600784430","https://openalex.org/W6669568774"],"related_works":["https://openalex.org/W3201688424","https://openalex.org/W2022867152","https://openalex.org/W2048800900","https://openalex.org/W4381431108","https://openalex.org/W2931607628","https://openalex.org/W755050109","https://openalex.org/W3006471751","https://openalex.org/W2410415934","https://openalex.org/W2126524872","https://openalex.org/W3200938883"],"abstract_inverted_index":{"This":[0],"research":[1],"aimed":[2],"to":[3,30,39,55,90],"evaluate":[4],"the":[5,8,13,16,32,41,43,57,72,79,86,92,111,114,122,130,133,149],"performance":[6,131,152],"of":[7,51,59,66,124,132],"statistical":[9,134],"control":[10,136],"charts":[11,67],"under":[12,137],"situation":[14],"that":[15,78,118],"observations":[17],"were":[18],"correlated.":[19],"The":[20,48,74],"autoregressive":[21],"moving":[22,82],"average":[23,44,83],"model,":[24],"ARMA":[25,63,93],"(1,":[26,94],"1),":[27],"was":[28,37,53,85],"utilized":[29],"characterize":[31],"disturbances.":[33],"A":[34],"process":[35,135],"model":[36],"simulated":[38],"achieve":[40],"response,":[42],"run":[45],"length":[46],"(ARL).":[47],"factorial":[49],"design":[50],"experiment":[52],"conducted":[54],"define":[56],"impacts":[58],"critical":[60],"factors":[61],"e.g.":[62],"coefficients,":[64],"types":[65],"and":[68,100],"shift":[69,105],"sizes":[70,106],"on":[71,110],"ARL.":[73,112],"experimental":[75],"results":[76,116],"showed":[77],"exponentially":[80],"weighted":[81],"(EWMA)":[84],"most":[87],"appropriate":[88],"chart":[89],"monitor":[91],"1)":[95],"observations.":[96],"Additionally,":[97],"both":[98],"AR":[99],"MA":[101],"parameters":[102],"along":[103],"with":[104],"had":[107],"significant":[108],"effects":[109],"Therefore,":[113],"available":[115],"indicated":[117],"conditions":[119],"at":[120],"which":[121],"minimization":[123],"ARL":[125],"can":[126],"be":[127],"achieved.":[128],"If":[129],"stationary":[138],"disturbances":[139],"is":[140],"correctly":[141],"characterized,":[142],"practitioners":[143],"will":[144],"have":[145],"guidelines":[146],"for":[147],"achieving":[148],"highest":[150],"possible":[151],"potential":[153],"when":[154],"deploying":[155],"SPC.":[156]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}