dc.contributor | Universidade Estadual Paulista (UNESP) | |
dc.creator | Costa, A. F. B. | |
dc.creator | Machado, M. A. G. | |
dc.date | 2014-05-20T13:28:31Z | |
dc.date | 2016-10-25T16:48:12Z | |
dc.date | 2014-05-20T13:28:31Z | |
dc.date | 2016-10-25T16:48:12Z | |
dc.date | 2009-04-01 | |
dc.date.accessioned | 2017-04-05T20:11:36Z | |
dc.date.available | 2017-04-05T20:11:36Z | |
dc.identifier | International Journal of Advanced Manufacturing Technology. Artington: Springer London Ltd, v. 41, n. 7-8, p. 770-779, 2009. | |
dc.identifier | 0268-3768 | |
dc.identifier | http://hdl.handle.net/11449/9498 | |
dc.identifier | http://acervodigital.unesp.br/handle/11449/9498 | |
dc.identifier | 10.1007/s00170-008-1502-9 | |
dc.identifier | WOS:000264136500016 | |
dc.identifier | http://dx.doi.org/10.1007/s00170-008-1502-9 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/857650 | |
dc.description | In this article, we propose a control chart for detecting shifts in the covariance matrix of a multivariate process. The monitoring statistic is based on the standardized sample variance of p quality characteristics we call the VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these p variances. The reasons to consider the VMAX statistic instead of the generalized variance |S| are faster detection of process changes and better diagnostic features, which mean that the VMAX statistic is better at identifying the out-of-control variable. User's familiarity with sample variances is another point in favor of the VMAX statistic. An example is presented to illustrate the application of the proposed chart. | |
dc.description | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
dc.description | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.language | eng | |
dc.publisher | Springer London Ltd | |
dc.relation | International Journal of Advanced Manufacturing Technology | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | Control charts | |
dc.subject | Multivariate processes | |
dc.subject | Covariance matrix | |
dc.subject | Generalized variance | |
dc.title | A new chart based on sample variances for monitoring the covariance matrix of multivariate processes | |
dc.type | Otro | |