Matches in SemOpenAlex for { <https://semopenalex.org/work/W4283070505> ?p ?o ?g. }
- W4283070505 endingPage "3484" @default.
- W4283070505 startingPage "3470" @default.
- W4283070505 abstract "Abstract Some researchers have incorrectly concluded that the geometric CUSUM is superior to the Bernoulli CUSUM as a procedure for monitoring a repetitive process, even though the two procedures have been proved to be equivalent for detecting an upward shift in the proportion of nonconforming items. We use an exact Markov‐chain‐based methodology to re‐examine the relationship between geometric CUSUM and Bernoulli CUSUM control charts. Exact methods allow us to differentiate between similar but different‐valued quantities that have contributed to some misunderstandings in the literature. We show that for a random‐shift model, evaluations of steady‐state average number of inspected items until a signal (ANIs) are identical for both geometric CUSUMs and Bernoulli CUSUMs, provided the correct choices of return levels are made. We also show that a steady‐state geometric CUSUM based on a fixed‐shift model only uses the geometric CUSUM states, while a steady‐state geometric CUSUM based on a random‐shift model will reach the states of a Bernoulli CUSUM after a long series of zeros. We note that our conclusions are contrary to the published results of other researchers, and we examine these differences in detail. Layman's Abstract: Since, their introduction by Walter Shewhart in 1931, control charts such as the Shewhart p ‐chart have had widespread application for monitoring the output quality from manufacturing processes, such as the proportion ( p ) in the stream of manufactured items that are nonconforming. But the Shewhart p ‐chart is not very effective for monitoring processes when the proportion p is less than about 4 percent. Other charts, such as the geometric CUSUM (proposed in 1991) and the Bernoulli CUSUM (proposed in 1999) have been shown to be superior at identifying changes in p when p is small. Some researchers have relied on simulation‐based investigations to compare these two CUSUMs, and have incorrectly concluded that the geometric CUSUM is superior to the Bernoulli CUSUM, even though the two procedures have been proved to be equivalent for detecting an upward shift in the proportion p . Using exact, Markov‐chain‐based methodology, we re‐examine the relationship between the geometric CUSUM and the Bernoulli CUSUM control charts and demonstrate that these two charts are equivalent when evaluated correctly. Exact methods allow us to precisely compare these two monitoring schemes and correct some erroneous conclusions that have appeared in the literature." @default.
- W4283070505 created "2022-06-19" @default.
- W4283070505 creator A5006292572 @default.
- W4283070505 creator A5039510217 @default.
- W4283070505 creator A5042128948 @default.
- W4283070505 creator A5048319335 @default.
- W4283070505 creator A5006843090 @default.
- W4283070505 date "2022-06-17" @default.
- W4283070505 modified "2023-09-26" @default.
- W4283070505 title "A closer look at the equivalence of Bernoulli and geometric CUSUM control charts" @default.
- W4283070505 cites W107240477 @default.
- W4283070505 cites W164102641 @default.
- W4283070505 cites W1921279082 @default.
- W4283070505 cites W1936325951 @default.
- W4283070505 cites W1992345453 @default.
- W4283070505 cites W2010247739 @default.
- W4283070505 cites W2018319586 @default.
- W4283070505 cites W2042948051 @default.
- W4283070505 cites W2043581342 @default.
- W4283070505 cites W2049611308 @default.
- W4283070505 cites W2056821499 @default.
- W4283070505 cites W2073223972 @default.
- W4283070505 cites W2343606688 @default.
- W4283070505 cites W2793285303 @default.
- W4283070505 cites W2802629250 @default.
- W4283070505 cites W3197274529 @default.
- W4283070505 cites W3213078993 @default.
- W4283070505 cites W4214824791 @default.
- W4283070505 cites W4231783271 @default.
- W4283070505 cites W4242238626 @default.
- W4283070505 cites W4244700351 @default.
- W4283070505 cites W4249116379 @default.
- W4283070505 cites W4250232021 @default.
- W4283070505 cites W4367275842 @default.
- W4283070505 cites W47082858 @default.
- W4283070505 cites W98139959 @default.
- W4283070505 cites W988335224 @default.
- W4283070505 doi "https://doi.org/10.1002/qre.3145" @default.
- W4283070505 hasPublicationYear "2022" @default.
- W4283070505 type Work @default.
- W4283070505 citedByCount "0" @default.
- W4283070505 crossrefType "journal-article" @default.
- W4283070505 hasAuthorship W4283070505A5006292572 @default.
- W4283070505 hasAuthorship W4283070505A5006843090 @default.
- W4283070505 hasAuthorship W4283070505A5039510217 @default.
- W4283070505 hasAuthorship W4283070505A5042128948 @default.
- W4283070505 hasAuthorship W4283070505A5048319335 @default.
- W4283070505 hasConcept C105795698 @default.
- W4283070505 hasConcept C111919701 @default.
- W4283070505 hasConcept C118615104 @default.
- W4283070505 hasConcept C127413603 @default.
- W4283070505 hasConcept C146978453 @default.
- W4283070505 hasConcept C152361515 @default.
- W4283070505 hasConcept C159848633 @default.
- W4283070505 hasConcept C167779127 @default.
- W4283070505 hasConcept C178518018 @default.
- W4283070505 hasConcept C190812933 @default.
- W4283070505 hasConcept C196985124 @default.
- W4283070505 hasConcept C23990920 @default.
- W4283070505 hasConcept C2780069185 @default.
- W4283070505 hasConcept C28826006 @default.
- W4283070505 hasConcept C33923547 @default.
- W4283070505 hasConcept C41008148 @default.
- W4283070505 hasConcept C74746147 @default.
- W4283070505 hasConcept C98045186 @default.
- W4283070505 hasConcept C98763669 @default.
- W4283070505 hasConceptScore W4283070505C105795698 @default.
- W4283070505 hasConceptScore W4283070505C111919701 @default.
- W4283070505 hasConceptScore W4283070505C118615104 @default.
- W4283070505 hasConceptScore W4283070505C127413603 @default.
- W4283070505 hasConceptScore W4283070505C146978453 @default.
- W4283070505 hasConceptScore W4283070505C152361515 @default.
- W4283070505 hasConceptScore W4283070505C159848633 @default.
- W4283070505 hasConceptScore W4283070505C167779127 @default.
- W4283070505 hasConceptScore W4283070505C178518018 @default.
- W4283070505 hasConceptScore W4283070505C190812933 @default.
- W4283070505 hasConceptScore W4283070505C196985124 @default.
- W4283070505 hasConceptScore W4283070505C23990920 @default.
- W4283070505 hasConceptScore W4283070505C2780069185 @default.
- W4283070505 hasConceptScore W4283070505C28826006 @default.
- W4283070505 hasConceptScore W4283070505C33923547 @default.
- W4283070505 hasConceptScore W4283070505C41008148 @default.
- W4283070505 hasConceptScore W4283070505C74746147 @default.
- W4283070505 hasConceptScore W4283070505C98045186 @default.
- W4283070505 hasConceptScore W4283070505C98763669 @default.
- W4283070505 hasIssue "7" @default.
- W4283070505 hasLocation W42830705051 @default.
- W4283070505 hasOpenAccess W4283070505 @default.
- W4283070505 hasPrimaryLocation W42830705051 @default.
- W4283070505 hasRelatedWork W1507167546 @default.
- W4283070505 hasRelatedWork W173161442 @default.
- W4283070505 hasRelatedWork W19159520 @default.
- W4283070505 hasRelatedWork W1979919906 @default.
- W4283070505 hasRelatedWork W2027023516 @default.
- W4283070505 hasRelatedWork W2037626511 @default.
- W4283070505 hasRelatedWork W2181580412 @default.
- W4283070505 hasRelatedWork W2213954818 @default.
- W4283070505 hasRelatedWork W2931607628 @default.