Statistical Process Control of Multivariate Processes

Survey on data-driven industrial process monitoring and diagnosis

Publisher Summary Circular dichroism (CD) is a spectroscopic method which depends on the fact that certain molecules interact differently with right and left circularly polarized light. Circularly polarized light is chiral—that is, it occurs in two nonsuperimposable forms that are mirror images of one another. To discriminate between the two chiral forms of light, a molecule must be chiral, including the vast majority of biological molecules. A method that can discern the subtle differences between non superimposable mirror image molecules (enantiomers) must be highly sensitive to the three-dimensional features of molecules—that is, to conformation. Binding of ligands or protein-protein and protein–DNA interactions can also alter the circular dichroism spectrum of the protein and/or nucleic acid. These changes in CD can be used to determine equilibrium constants, and they can also provide evidence for conformational changes. Thus, CD can provide information about the secondary structure of proteins and nucleic acids and about the binding of ligands to these types of macromolecule.

[4] Circular dichroism

The process chemometrics approach to process monitoring and fault detection

No wonder you activities are, reading will be always needed. It is not only to fulfil the duties that you need to finish in deadline time. Reading will encourage your mind and thoughts. Of course, reading will greatly develop your experiences about everything. Reading molecular biology of the gene is also a way as one of the collective books that gives many advantages. The advantages are not only for you, but for the other peoples with those meaningful benefits.

Molecular Biology of the Gene.

Producing a uniform polymer by batch processing is important for the following reasons: to improve the downstream processing performance, to enable material produced at one site to be used by another, and to remain competitive Eliminating the sources of batch-to-batch variability and tightening the control of key variables are but two ways to accomplish these objectives In this work, it is shown that multiway principal component analysis (MPCA) can be used to identify major sources of variability in the processing steps The results show that the major source of batch-to-batch variability is due to reactor temperature variations arising from disturbances in the heating system and other heat-transfer limitations Correlations between the variations in the processing steps and the final product properties are found, and recommendations to reduce the sources of variations are discussed

Improved Process Understanding Using Multiway Principal Component Analysis

Circular dichroism spectra are calculated for 68 different conformations of the bases in the double-stranded sequence of T-G-G-C-G-T-A-T-T-C-T and its complementary strand. All conformations are right-handed helices and include both published models and energy-minimized forms. Examination of the dependence of the circular dichroism band at 274 nm shows that the magnitude of the band is a linear function of both the helix winding angle and the base pair twist. Correlations of the magnitude of the circular dichroism with the distance between base pairs, the distance of the base pairs from the helix axis, or the tilt of the base pair relative to the helix axis are poorer.

Correlations between deoxyribonucleic acid structural parameters and calculated circular dichroism spectra.

Batch and semi-batch processes are common in most chemical companies. These processes are characterized by a prescribed processing of materials for a finite duration of time. Feedback control often cannot be applied to correct for disturbances in a timely manner during the batch. Techniques which can provide insights into correlations among variables and their relationships to product quality will provide insights in the design of a control strategy that may improve product quality and minimize batch to batch variations. In this paper, the authors apply the statistical technique of multi-way principal component analysis to analyze the data from an industrial batch process. Using this technique, the authors were able to associate several significant causes of variability with the recipe imposed by the process. This information gave rise to a different control strategy which is presented. Subtle effects among batches were also uncovered and identified.

Multi-way PCA applied to an industrial batch process

A computer- implemented system and method for converting the resistances of an array of metal oxide sensors into constituents and concentrations of a multi-component gas provided around the sensor array. The method includes providing a self-diagnostic module to calculate the quality factors associated with corresponding prediction models and determine if the response of the sensor array are within a preferrred range; and providing a concentration calculation module to calculate the gas concentration outputs from each prediction model, corresponding tolerance limits, and gas concentration outputs determined by weighting the outputs from the prediction models by corresponding quality factors and determining the weighted tolerance limits, so that the gas concentration outputs with the lowest tolerance limits can be reported as the actual constituents and concentrations of the multi-component gas .

Kenneth S. Dahl

Papers

Improved Process Understanding Using Multiway Principal Component Analysis

Correlations between deoxyribonucleic acid structural parameters and calculated circular dichroism spectra.

Multi-way PCA applied to an industrial batch process

Computer-implemented system and method for analyzing mixtures of gases

Translating third-order data analysis methods to chemical batch processes