The economic design of multivariate binomial EWMA VSSI control charts
Seyed Taghi Akhavan Niaki and
Paravaneh Jahani
Journal of Applied Statistics, 2013, vol. 40, issue 6, 1301-1318
Abstract:
Since multi-attribute control charts have received little attention compared with multivariate variable control charts, this research is concerned with developing a new methodology to employ the multivariate exponentially weighted moving average (MEWMA) charts for m -attribute binomial processes; the attributes being the number of nonconforming items. Moreover, since the variable sample size and sampling interval (VSSI) MEWMA charts detect small process mean shifts faster than the traditional MEWMA, an economic design of the VSSI MEWMA chart is proposed to obtain the optimum design parameters of the chart. The sample size, the sampling interval, and the warning/action limit coefficients are obtained using a genetic algorithm such that the expected total cost per hour is minimized. At the end, a sensitivity analysis has been carried out to investigate the effects of the cost and the model parameters on the solution of the economic design of the VSSI MEWMA chart.
Date: 2013
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/02664763.2013.785494 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:40:y:2013:i:6:p:1301-1318
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/02664763.2013.785494
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().