TY - JOUR
ID - 3364
TI - Fuzzy Development of Multivariate Variable Control Charts Using the Fuzzy Likelihood Ratio Test
JO - Scientia Iranica
JA - SCI
LA - en
SN - 1026-3098
AU - Moheb Alizadeh, H.
AU - Arshadi Khamseh, A. R.
AU - Fatemi Ghomi, S. M. T.
AD - Department of Industrial Engineering,Tarbiat Modares University
AD - Department of Industrial Engineering,Amirkabir University of Technology
Y1 - 2010
PY - 2010
VL - 17
IS - 2
SP -
EP -
KW - Multivariate control charts
KW - Likelihood ratio test
KW - non-linear programming
KW - Fuzzy numbers
KW - fuzzy random variables
DO -
N2 - This paper is an eort to evolve multivariate variable control charts in a fuzzy environment
where each observation in each sample is assumed to be a canonical fuzzy number. To do this, a likelihood
ratio test should be exploited in a fuzzy environment, because multivariate variable control charts are
constructed using this test. In this way, membership functions of likelihood ratio statistics applied to
control the process mean and dispersion are obtained solving four non-linear programming problems. Using
these membership functions, membership degrees of in and out of control states of both process mean and
dispersion are computed. Hence contrary to the classic multivariate variable control charts categorizing the
process into just two states, i.e. in and out of control, the process can be considered in several intermediate
states, based on the computed membership degrees, bringing about more
exibility in process analysis.
UR - https://scientiairanica.sharif.edu/article_3364.html
L1 - https://scientiairanica.sharif.edu/article_3364_bfe02d2f742c0d69c75026ccdb0c6a7e.pdf
ER -