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Multivariate statistical process control (MSPC) tools have been developed for monitoring a Lam 9600 TCP metal etcher at Texas Instruments. These tools are used to determine if the etch process is operating normally or if a system fault has occurred. Application of these methods is complicated because the etch process data exhibit a large amount of normal systematic variation. Variations due to faults of process concern can be relatively minor in comparison. The Lam 9600 used in this study is equipped with several sensor systems including engineering variables (e.g. pressure, gas flow rates and power), spatially resolved optical emission spectroscopy (OES) of the plasma and a radio‐frequency monitoring (RFM) system to monitor the power and phase relationships of the plasma generator. A variety of analysis methods and data preprocessing techniques have been tested for their sensitivity to specific system faults. These methods have been applied to data from each of the sensor systems separately and in combination. The performance of the methods on a set of benchmark fault detection problems is presented and the strengths and weaknesses of the methods are discussed, along with the relative advantages of each of the sensor systems. Copyright © 1999 John Wiley & Sons, Ltd.

Physical properties, including amyloid morphology, FTIR and CD spectra, enhancement of Congo red absorbance, polymerization rate, critical monomer concentration, free energy of stabilization, hydrophobicity, and the partition coefficient between soluble and amyloid states, were measured for the tau-related peptide Ac-VQIVYK amide (AcPHF6) and its single site mutants Ac-VQIVXK amide (X not equal Cys). Transmission electron microscopy showed that 15 out of the 19 peptides formed amyloid in buffer, with morphologies ranging from straight and twisted filaments to sheets and rolled sheets. Using principal component analysis (PCA), measured properties were treated in a comprehensive manner, and scores along the most significant principal components were used to define individual amino acid amyloidogenic propensities. Quantitative structure-activity modeling (QSAM) showed that residues with greater size and hydrophobicity made the largest contributions to the propensity of peptides to form amyloid. Using individual amino acid propensities, sequences within tau with high amyloid-forming potential were estimated and found to include 226VAVVR230 in the proline-rich region, 275VQIINK280 (PHF6) and 306VQIVYK311 (PHF6) within the microtubule binding region, and 392IVYK395 in the C-tail region of the protein. The results suggest that regions outside the microtubule-binding region may play important roles in tau aggregation kinetics or paired helical filament structure.