MONITORING AND IDENTIFICATION OF INFLUENTIAL PROCESS CHARACTERISTICS IN THE PRESENCE OF AUTOCORRELATION
MONITORING AND IDENTIFICATION OF INFLUENTIAL PROCESS CHARACTERISTICS IN THE PRESENCE OF AUTOCORRELATION
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Date
2015-12
Authors
ADEPOJU, AKEEM AJIBOLA
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Abstract
The traditional methods of multivariate statistical process control (MSPC) are primarily based
on the assumptions that the successive observation vectors are independent and normally
distributed.However, some process observations are found to be dependent (known as
autocorrelation or serial correlation) and if the autocorrelation is left untreated, this can
consequently lead to wrong monitoring decision as well as wrong variable identification in the
case of out-of-control, which consequently affect the performance of the control charts. This
thesis looked into the problem of monitoring the mean vector of a process embedded with
autocorrelation and failure of normality assumption. In order to remove the autocorrelation effect
and normalized the original data, we proposed vector autoregressive model,VAR model whose
residual is assumed to be independent and Johnson transformation(JT) to transform the original
data to normality. We were able to show and compare the effect of applying traditional
Hotelling’s 2 T control chart on autocorrelated and non-normal data as against the
residualsobtained from VAR (1) model and normally transformed data. However, since our
intention is to achieve a better decision in industrial settings, we thereby complement this work
by further adopted MYT model to decompose the overall contribution of the five process
variables into individual contribution such that the influential variable(s) is/are identified
Description
A THESIS SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES, AHMADU BELLO UNIVERSITY, ZARIA NIGERIA IN PARTIAL FULFILLMENT FOR THE AWARD OF MASTER OF SCIENCE (M.Sc) DEGREE IN STATISTICS, DEPARTMENT OF MATHEMATICS AHMADU BELLO UNIVERSITY, ZARIA NIGERIA
Keywords
MONITORING,, IDENTIFICATION,, INFLUENTIAL PROCESS CHARACTERISTICS,, PRESENCE,, AUTOCORRELATION,