Condition Monitoring of Casting Process usingMultivariate Statistical Method

Thus, in order to identify the models describing the parameter dynamics, statistical inference estimation methods such as the maximum likelihood method and the

Les groupes quantiques sont apparus pour la premi`ere fois dans la th´eorie des syst`emes int´egrables et la th´eorie des mod`eles statistiques exactement solubles sur des

The obtained decomposition levels are used as input to the PCA method for fault identification using respectively, the Q-statistic, it is also called Squared

Finally, we prove that conditioning a multitype branching process on having an infinite total progeny leads to a process presenting the features of a Q-process.. It does not

This study will mainly investigate a technique based on principal component analysis in order to improve the accuracy for fault diagnosis of casting process. The

Keywords : fault detection and diagnosis, principal component analysis, multivariate statistical process control, T2-statistic, Q-statistic, squared prediction error,

Keywords: fault detection and diagnosis, principal component analysis, multivariate statistical process control, T 2 -statistic, Q-statistic, squared prediction

Statistical timing analysis models delay arcs as random variables and propagate timing constraints using probability distribution functions (pdfs).. While a substantial focus has