Data integration for the monitoring of batch processes in the pharmeceutical industry

PhD ThesisAdvances in sensor technology has resulted in large amounts of data being available electronically. However, to utilise the potential of the data, there is a need to transform the data into knowledge to realise an enhanced understanding of the process. This thesis investigates a number of multivariate statistical projection techniques for the monitoring of batch fermentation and pharmaceutical processes. In the first part of the thesis, the traditional performance monitoring tools based on the approaches of Nomikos and MacGregor (1994) and Wold et al. (1998) are introduced. Additionally, the application of data scaling as a data pre-treatment step for batch processes is examined and it is observed that it has a significant impact on monitoring performance. Based on the advantages and limitations of these techniques, an alternative methodology is proposed and applied to a simulated penicillin fermentation process. The approach is compared with existing techniques using two metrics, false alarm rate and out-ofcontrol average run length. A further manufacturing challenge facing the pharmaceutical industry is to understand the differences in the performance of a product which is manufactured at two or more sites. A retrospective multi-site monitoring model is developed utilising a pooled sample variancecovariance methodology of the two sites. The results of this approach are compared with a number of techniques that have been previously reported in the literature for the integration of data from two or more sources. The latter part of the thesis focuses on data integration using multi-block analysis. Several blocks of data can be analysed simultaneously to allow the inter- and intra- block relationships to be extracted. The methodology of multi-block Principal Component Analysis (MBPCA) is initially reviewed. To enhance the sensitivity of the algorithm, wavelet analysis is incorporated within the MBPCA framework. The fundamental advantage of wavelet analysis is its ability to process a signal at different scales so that both the global features and the localised details of a signal can be studied simultaneously. Both existing and the modified approach are applied to data generated from an experiment conducted in a batch mini-plant and that was monitored by both physical sensors and on-line UV-Visible spectrometer. The performance of the integrated approaches is benchmarked against the individual process and spectral monitoring models as well as examining their fault detection ability on two additional batches with pre-designed process deviations.Engineering and Physical Sciences Research Council (EPSRC: The Overseas Research Students Award Scheme (ORSAS): The Centre for Process Analytics and Control Technology (CPACT)

Data integration for the monitoring of batch processes in the pharmaceutical industry

Advances in sensor technology has resulted in large amounts of data being available electronically. However, to utilise the potential of the data, there is a need to transform the data into knowledge to realise an enhanced understanding of the process. This thesis investigates a number of multivariate statistical projection techniques for the monitoring of batch fermentation and pharmaceutical processes. In the first part of the thesis, the traditional performance monitoring tools based on the approaches of Nomikos and MacGregor (1994) and Wold et al. (1998) are introduced. Additionally, the application of data scaling as a data pre-treatment step for batch processes is examined and it is observed that it has a significant impact on monitoring performance. Based on the advantages and limitations of these techniques, an alternative methodology is proposed and applied to a simulated penicillin fermentation process. The approach is compared with existing techniques using two metrics, false alarm rate and out-ofcontrol average run length. A further manufacturing challenge facing the pharmaceutical industry is to understand the differences in the performance of a product which is manufactured at two or more sites. A retrospective multi-site monitoring model is developed utilising a pooled sample variancecovariance methodology of the two sites. The results of this approach are compared with a number of techniques that have been previously reported in the literature for the integration of data from two or more sources. The latter part of the thesis focuses on data integration using multi-block analysis. Several blocks of data can be analysed simultaneously to allow the inter- and intra- block relationships to be extracted. The methodology of multi-block Principal Component Analysis (MBPCA) is initially reviewed. To enhance the sensitivity of the algorithm, wavelet analysis is incorporated within the MBPCA framework. The fundamental advantage of wavelet analysis is its ability to process a signal at different scales so that both the global features and the localised details of a signal can be studied simultaneously. Both existing and the modified approach are applied to data generated from an experiment conducted in a batch mini-plant and that was monitored by both physical sensors and on-line UV-Visible spectrometer. The performance of the integrated approaches is benchmarked against the individual process and spectral monitoring models as well as examining their fault detection ability on two additional batches with pre-designed process deviations.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (EPSRC) : Overseas Research Students Award Scheme (ORSAS) : Centre for Process Analytics and Control Technology (CPACT)GBUnited Kingdo

Políticas de amostragem em controlo estatístico da qualidade

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Statistics and EconometricsNesta Dissertação apresentam-se e estudam-se, de uma forma crítica, dois novos métodos de amostragem adaptativa e uma nova medida de desempenho de métodos de amostragem, no contexto do controlo estatístico da qualidade. Considerando como base uma carta de controlo para a média do tipo Shewhart, estudamos as suas propriedades estatísticas e realizamos estudos comparativos, em termos do seu desempenho estatístico, com alguns dos métodos mais referenciados na literatura.Inicialmente, desenvolvemos um novo método adaptativo de amostragem no qual os intervalos entre amostras são obtidos com base na função densidade da distribuição de Laplace reduzida. Este método revela-se, particularmente, eficiente na deteção de moderadas e grandes alterações da média, pouco sensível à limitação do menor intervalo de amostragem e robusto face a diferentes situações consideradas para a não normalidade da característica da qualidade. Em determinadas situações, este método é sempre mais eficiente do que o método com intervalos de amostragem adaptativos,dimensões amostrais fixas e coeficientes dos limites de controlo fixos. Tendo como base o método de amostragem definido no ponto anterior e um método no qual os intervalos de amostragem são definidos antes do início do controlo do processo com base na taxa cumulativa de risco do sistema, apresentamos um novo método de amostragem que combina o método de intervalos predefinidos com o método de intervalos adaptativos. Neste método, os instantes de amostragem são definidos pela média ponderada dos instantes dos dois métodos, atribuindo-se maior peso ao método adaptativo para alterações moderadas (onde o método predefinido é menos eficaz) e maior peso ao método predefinido nos restantes casos (onde o método adaptativo é menos eficaz). Desta forma, os instantes de amostragem, inicialmente calendarizados de acordo com as expectativas de ocorrência de uma alteração tomando como base a distribuição do tempo de vida do sistema, são adaptados em função do valor da estatística amostral calculada no instante anterior. Este método é sempre mais eficiente do que o método periódico clássico, o que não acontece com nenhum outro esquema adaptativo, e do que o método de amostragem VSI para alguns pares de amostragem, posicionando-se como uma forte alternativa aos procedimentos de amostragem encontrados na literatura. Por fim, apresentamos uma nova medida de desempenho de métodos de amostragem. Considerando que dois métodos em comparação têm o mesmo tempo médio de mau funcionamento, o desempenho dos métodos é comparado através do número médio de amostras recolhidas sob controlo. Tendo em conta o tempo de vida do sistema, com diferentes taxas de risco, esta medida mostra-se robusta e permite, num contexto económico, um melhor controlo de custos por unidade de tempo

A collaborative, multi-agent based methodology for abnormal events management

Ph.DDOCTOR OF PHILOSOPH

Economic Structural Change: Analysis and Forecasting

In modern economic model building, structural change is a key concept. Economic growth and events like the oil price shocks have impacts on the economic system such that models with fixed structure are illusions. Considerable progress has been made in the last few years concerning statistical and econometric tools. Methods for identification of structural change, models that are robust to changes and assimilate their effects, and adequate forecasting techniques have been developed. Under the auspices of IIASA a very active community of statisticians and econometricians has made a very influential effort in this area. The purpose of this volume is to document these activities, to present new methods and developments in this area, and to demonstrate applications. Particular weight is given to nonparametric and robust methods for identification of and modeling under structural change, a Bayesian approach to forecast combination, and time-varying parameter cointegration. This book has four parts: (1) Identification of structural change, (2) Model building in the presence of structural change, (3) Forecasting in the presence of structural change, and (4) Economic modeling and the use of empirical data. The book provides an up-to-date status report on the field and should stimulate applications of the methods in empirical work as well as further research