Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEEM.2009.5373319
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dc.titleA MEWMA chart for a bivariate exponential distribution
dc.contributor.authorXie, Y.J.
dc.contributor.authorXie, M.
dc.contributor.authorGoh, T.N.
dc.date.accessioned2014-06-19T04:52:44Z
dc.date.available2014-06-19T04:52:44Z
dc.date.issued2009
dc.identifier.citationXie, Y.J., Xie, M., Goh, T.N. (2009). A MEWMA chart for a bivariate exponential distribution. IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management : 424-428. ScholarBank@NUS Repository. https://doi.org/10.1109/IEEM.2009.5373319
dc.identifier.isbn9781424448708
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/72244
dc.description.abstractControl charts as one of the most well-known statistical process control (SPC) techniques have shown to be effective in process monitoring. Most of the existing studies in the area of the time-between-event (TBE) control charts have been focused on the univariate cases. In this paper, a MEWMA chart is constructed for monitoring the mean vector of the Gumbel's bivariate exponential TBE model. The average run length profile of the proposed chart is studied using simulation. Some guidelines for setting up an optimal MEWMA chart are provided. Finally, a numerical example is given to show the effectiveness of the MEWMA chart. ©2009 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/IEEM.2009.5373319
dc.sourceScopus
dc.subjectARL
dc.subjectGumbel's bivariate exponential distribution
dc.subjectMEWMA chart
dc.typeConference Paper
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.description.doi10.1109/IEEM.2009.5373319
dc.description.sourcetitleIEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management
dc.description.page424-428
dc.identifier.isiut000280236600086
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