in some statistical process control applications, the quality of the product is characterized by thecombination of both correlated variable and attributes quality characteristics. in this paper, we propose anovel control scheme based on the combination of two multi-layer perceptron neural networks forsimultaneous monitoring of mean vector as well as the covariance matrix in multivariate-attribu...

The primary objective of this note is to reduce the false alarms in multivariate statistical process control (MSPC). The issue of false alarms is inherent within MSPC as a result of the definition of control limits. It has been observed that under normal operating conditions, the occurrence of “outof-control” data, i.e. false alarms, conforms to a Bernoulli distribution. Therefore this issue ca...

Hyung Dae Jin, Young-Hak Lee and Chonghun Han Department of Chemical Engineering, Pohang University of Science & Technology, San 31, Hyoja, Pohang, Kyungbuk, 790-784, Korea 2 Automation and Systems Research Institute, Seoul National University, San 56-1, Shillimdong, Kwanak-gu, Seoul, 151-742, Korea 3 School of Chemical Engineering, Seoul National University, San 56-1, Shillim-dong, Kwanak-gu, ...

Although refractory epileptic patients suffer from uncontrolled seizures, their quality of life (QoL) may be improved if the seizure can be predicted in advance. In the preictal period, the excessive neuronal activity of epilepsy affects the autonomic nervous system. Since the fluctuation of the R-R interval (RRI) of an electrocardiogram (ECG), called heart rate variability (HRV), reflects the ...

Abstract: Monitoring process upsets and malfunctions as early as possible and then finding and removing the factors causing the respective events is of great importance for safe operation and improved productivity. Conventional process monitoring using principal component analysis (PCA) often supposes that process data follow a Gaussian distribution. However, this kind of constraint cannot be s...

Multivariate Process Capability Indices (MPCI) show how well a manufacturing process can meet specifica-tion limits when quality characteristics enclose a relative correlation. Process capability is an important and commonly used metric for assessing and improving the quality of a production process. When quality charac-teristics of a product are correlated then an attractive comes close to MPC...

Multivariate statistical methods for the analysis, monitoring and diagnosis of process operating performance are becoming more important because of the availability of on-line process computers which routinely collect measurements on large numbers of process variables. Traditional univariate control charts have been extended to multivariate quality control situations using the Hotelling T2 stat...