Please use this identifier to cite or link to this item: https://doi.org/10.1080/02664760701546279
DC FieldValue
dc.titleModified shewhart charts for high yield processes
dc.contributor.authorChang, T.C.
dc.contributor.authorGan, F.F.
dc.date.accessioned2014-10-28T05:17:00Z
dc.date.available2014-10-28T05:17:00Z
dc.date.issued2007-09
dc.identifier.citationChang, T.C., Gan, F.F. (2007-09). Modified shewhart charts for high yield processes. Journal of Applied Statistics 34 (7) : 857-877. ScholarBank@NUS Repository. https://doi.org/10.1080/02664760701546279
dc.identifier.issn02664763
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105500
dc.description.abstractThe conventional Shewhart p or np chart is not effective for monitoring a high yield process, a process in which the defect level is close to zero. An improved Shewhart np chart for monitoring high yield processes is proposed. A review of control charts for monitoring high yield processes is first given. The run length performance of the proposed Shewhart chart is then compared with other high yield control charts. A simple procedure for designing the chart for processes subjected to sampling or 100% continuous inspection is provided and this allows the chart to be implemented easily on the factory floor. The practical aspects of implementation of the Shewhart chart are discussed. An application of the Shewhart chart based on a real data set is demonstrated.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/02664760701546279
dc.sourceScopus
dc.subjectAverage run length
dc.subjectBinomial counts
dc.subjectParts-per-million non-conforming items
dc.subjectStatistical process control
dc.subjectSupplementary runs rules
dc.typeReview
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1080/02664760701546279
dc.description.sourcetitleJournal of Applied Statistics
dc.description.volume34
dc.description.issue7
dc.description.page857-877
dc.identifier.isiut000249261300008
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