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Virginia Tech

The Minimax control chart for multivariate quality control

Abstract

dc:description.abstract

A new multicharacteristic control chart designed to detect shifts in the mean of a multivariate process is proposed. It is assumed that the correlation matrix is known and that the distribution of the data is multivariate normal. The new chart is based on the minimum standardized sample mean (Z<sub>[1]</sub>) and the maximum standardized sample mean (Z<sub>[p]</sub>) of p correlated quality variables or characteristics. For this reason the chart has been named the Minimax control chart. A method for calculating probabilities for the joint distribution of Z<sub>[1]</sub> and Z<sub>[p]</sub> is developed. This method is used to determine the position of the four control limits of the chart; the upper and lower control limits of Z<sub>[1]</sub>, and the upper and lower control limits of Z<sub>[p]</sub>. The control limits of the chart are determined such that the chart has a fixed probability of Type I error. The chart’s performance is compared to that of the Chi-squared control chart in terms of the average run length for several combinations of the parameters of the chart. Among these parameters are the sample size, the number of variables, the probability of Type I error, the correlation matrix, and the direction and magnitude of the shift in the mean. The proposed chart outperforms the Chi-squared chart in all the cases studied where the covariance matrix has non-negative elements. The new chart provides an easy way for diagnosing the system when a signal occurs. That is to say, the chart provides a means to identify the source of the problem when a shift in the mean occurs. The criteria established for diagnosing the system is based on the positions of Z<sub>[1]</sub> and Z<sub>[p]</sub> in the Minimax chart. Thus, to diagnose the signals no further analysis is needed. The diagnosing criteria are shown to be particularly effective when the shifts in the mean are either axial or diagonal.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Industrial and Systems Engineering
Department dc:contributor.department
Industrial and Systems Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
1996

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sepúlveda, Ariel
Chair dc:contributor.committeechair
  • Nachlas, Joel A.
Committee members dc:contributor.committeemember
  • Schmidt, Joseph W.
  • Koelling, C. Patrick
  • Holtzman, Golde
  • Houck, Ernie

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
etd-12222005-090659
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/30230

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Sepúlveda, Ariel. The Minimax control chart for multivariate quality control. doctoral thesis, Virginia Tech, 1996. http://hdl.handle.net/10919/30230