In this work, the ethanol fuel dehydration process was optimized using Aspen Plus? simulator and a multivariate statistical technique based on desirability function. The suitability of ionic liquids 1-methylimidazolium chloride ([Mim][Cl]), 1-ethyl-3-methylimidazolium ([Emim][Cl]), 1-butyl- -3-methylimidazolium ([Bmim][Cl]) 1-hexyl-3-methylimidazolium ([Hmim][Cl]), as extractive distillation en...

in this paper, first the available single charting methods, which have been proposed to detect simultaneous shifts in a single process mean and variance, are reviewed. then, by designing proper simulation studies these methods are evaluated in terms of in-control and out-ofcontrol average run length criteria (arl). the results of these simulation experiments show that the ewma and ewms methods ...

Statistical process control (SPC) for injection molding typically consists of setting alarm limits on a few important molding variables for real-time part containment. A new multivariate statistical process control (MSPC) method is presented that utilizes the measurement of process variable relationships to achieve a more robust quality control system. This approach not only detects process out...

This paper proposes a distribution-free multivariate statistical process control (MSPC) chart to detect general distributional changes in multivariate process variables. The chart is deployed based on a multivariate goodness-of-fit test, which is extensible to high dimensional observations. The chart also employs data-dependent control limits, which are computed on line along with the charting ...

Multiscale Principal Component Analysis (MSPCA) combines the ability of PCA to decorrelate the variables by extracting a linear relationship, with that of wavelet analysis to extract deterministic features and approximately decorrelate autocorrelated measurements. MSPCA computes the PCA of the wavelet coefficients at each scale, followed by combining the results at relevant scales. Due to its m...

In this paper, a modified independent component analysis (ICA) and its application to process monitoring are proposed. The basic idea of this approach is to use the modified ICA to extract some dominant independent components from normal operating process data and to combine them with statistical process monitoring techniques. The proposed monitoring method is applied to fault detection and ide...