Monitoring of cure kinetic prepreg and cure cycle modeling

Cure kinetic model is an integral part of composite process simulation, which is used to predict the degree of curing and the amount of the generated heat. The parameters involved in kinetic models are usually determined empirically from isothermal or dynamic differential scanning calorimetry (DSC) data. In this work, DSC and rheological techniques were used to investigate some of the kinetic parameters of cure reactions of carbon/F161 epoxy prepreg and to evaluate the cure cycle used to manufacture polymeric composites for aeronautical applications. As a result, it was observed that the F161 prepreg presents cure kinetic with total order 1.2-1.9. (c) 2006 Springer Science + Business Media, Inc.

A control chart based on sample ranges for monitoring the covariance matrix of the multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new chart for monitoring the covariance matrix of bivariate processes

In this article we consider a control chart based on the sample variances of two quality characteristics. The points plotted on the chart correspond to the maximum value of these two statistics. The main reason to consider the proposed chart instead of the generalized variance |S| chart is its better diagnostic feature, that is, with the new chart it is easier to relate an out-of-control signal to the variables whose parameters have moved away from their in-control values. We study the control chart efficiency considering different shifts in the covariance matrix. In this way, we obtain the average run length (ARL) that measures the effectiveness of a control chart in detecting process shifts. The proposed chart always detects process disturbances faster than the generalized variance |S| chart. The same is observed when the size of the samples is variable, except in a few cases in which the size of the samples switches between small size and very large size.

The Synthetic Control Chart Based on Two Sample Variances for Monitoring the Covariance Matrix

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Economic-statistical design of the (X)over-bar chart used to control a wandering process mean using genetic algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Double sampling (x)over-bar control chart for a first-order autoregressive moving average process model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structural Health Monitoring in Smart Structures Through Time Series Analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

SAXS and UV-Vis combined to Quick-XAFS monitoring of ZnO nanoparticles formation and growth

Time-resolved X-ray absorption-fine structure (Quick-XAFS) and UV-Vis absorption spectroscopies were combined for monitoring simultaneously the time evolution of Zn-based species and ZnO quantum dot (Qdot) formation and growth during the sol-gel synthesis from zinc oxy-acetate precursor solution. The time evolution of the nanostructural features of colloidal suspension was independently monitored in situ by small angle X-ray scattering (SAXS). In both cases, the monitoring was initialized just after the addition of NaOH solution (B = [OH]/[Zn] = 0.5) to the precursor solution at 40 degrees C. Combined time-resolved Quick-XAFS and UV-Vis data showed that the formation of ZnO colloids from the zinc oxy-acetate consumption achieves a quasi-steady-state chemical equilibrium in less than 200s. Afterwards, the comparison of the ZnO Qdots size and Guinier gyration radius evidences a limited aggregation process coupled to the Qdots growth. The analysis of the experimental results demonstrates that the nanocrystal coalescence and Ostwald ripening control the kinetics of the Qdot growth.

Monitoring the mean vector and the covariance ­matrix of multivariate processes with sample means and sample ranges

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monitoring a wandering mean with an np chart

Este artigo considera um gráfico np x proposto por Wu et al. (2009) para controle de média de processo como uma alternativa ao uso do gráfico de. O que distingue do gráfico de controle np x é o fato das unidades amostrais serem classificadas como unidades de primeiro ou de segunda classe de acordo com seus limites discriminantes. O gráfico tradicional np é um caso particular do gráfico np x quando os limites discriminantes coincidem com os limites de especificação e unidade de primeira (segunda) classe é um item conforme (não conforme). Estendendo o trabalho de Reynolds Junior, Arnold e Baik (1996), consideramos que a média de processo oscila mesmo na ausência de alguma causa especial. As propriedades de Cadeia de Markov foram adotadas para avaliar o desempenho do gráfico np x no monitoramento de média de processos que oscila. de modo geral, o gráfico np x requer amostras duas vezes maior para superar desempenho do gráfico (enquanto que o gráfico tradicional np necessita tamanho de amostras cinco ou seis vezes maior).

Synthetic control chart for monitoring the pprocess mean and variance

In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.

Direct electron paramagnetic resonance monitoring of the peptide synthesis coupling reaction in polymeric support

This work demonstrates, for the first time. a time-resolved electron paramagnetic resonance (EPR) monitoring of a chemical reaction occurring in a polymeric structure. The progress of the coupling of a N-alpha-tert-butyloxycarbonyl-2.2.6.6-tetramethylpiperidine-1-oxyl-4-amino-4-carboxylic acid (Boc-TOAC) spin probe to a model peptide-resin was followed through EPR spectra. Progressive line broadening of EPR peaks was observed, indicative of an increased population of immobilized spin probe molecules attached to the solid support. The time for spectral stabilization of this process coincided with that determined in a previous Coupling study. thereby validating this in situ quantitative monitoring of the reaction. In addition, the influence of polymer swelling degree and solvent viscosity, as well as of the steric hindrance within beads. on the rate of coupling reaction was also addressed. A deeper evaluation of the latter effect was possible by determining unusual polymer parameters such as the average site-site distance and site-concentration within resin beads in each solvent system. (c) 2006 Elsevier Ltd. All rights reserved.

Dressing monitoring with a digital signal processor

Grinding is a finishing process in machining operations, and the topology of the grinding tool is responsible for producing the desired result on the surface of the machined material The tool topology is modeled in the dressing process and precision is therefore extremely important This study presents a solution in the monitoring of the dressing process, using a digital signal processor (DSP) operating in real time to detect the optimal dressing moment To confirm the monitoring efficiency by DSP, the results were compared with those of a data acquisition system (DAQ) and offline processing The method employed here consisted of analyzing the acoustic emission and electrical power signal by applying the DPO and DPKS parameters The analysis of the results allowed us to conclude that the application of the DPO and DPKS parameters can be substituted by processing of the mean acoustic emission signal, thus reducing the computational effort

In Situ and Simultaneous UV-vis/SAXS and UV-vis/XAFS Time-Resolved Monitoring of ZnO Quantum Dots Formation and Growth

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)