The focus of this thesis is on building models by utilizing process information: from data, from our knowledge of physics, or both. The closer the model approximates reality, the better is the expected performance in forecasting, soft-sensing, process monitoring, optimization and advanced process control. In the domain of batch and continuous manufacturing, quality models can help in ensuring tightly controlled product quality, having safe and reliable operating conditions and reducing production/operation costs. To this end, first a parallel grey box model was built which makes use of a mechanistic model, and a subspace identification model for modeling a batch poly methyl methacrylate (PMMA) polymerisation process. The efficacy of such a parallel hybrid model in the context of a control problem was illustrated thereafter for reducing the volume of fines. Real-time implementation of models in many cases demand the model to be tractable and simple enough, and thus the parallel hybrid model was next adapted to have a linear representation, and then used for control computations. While the parallel hybrid modelling strategy shows great advantages in many applications, there can be other avenues of using fundamental process knowledge in conjunction with historical data. In one such approach, a unique way of adding mechanistic knowledge to improve the estimation ability of PLS models was proposed. The predictor matrix of PLS was augmented with additional trajectory information coming strategically from a mechanistic model. This augmented model was used as a soft-sensor to estimate batch end quality for a seeded batch crystallizer process. In a collaborative work with an industrial partner focusing on estimating important variables of a hydroprocessing unit, an operational data based input-output model was chosen as the right fit in the absence of available mechanistic knowledge. The usefulness of linear dynamic modeling tools for such applications was demonstrated. / Thesis / Doctor of Philosophy (PhD)

La industria química ha experimentado en las últimas décadas un aumento en la competencia por la cual las empresas se ven obligadas a adaptarse a un mercado cambiante y cada vez más exigente. Aunque la globalización ha abierto nuevos mercados, ha incrementado también el número de competidores, de tal manera que sólo las empresas que usen las plantas más integradas y eficientes podrán mantenerse en el negocio. En este contexto global, el principal propósito de esta tesis es desarrollar métodos que exploten la flexibilidad de los procesos, con el objetivo de aumentar la eficiencia de las plantas y asegurar los requerimientos de seguridad y calidad de los productos. Esta tesis contribuye a la optimización y a la gestión de la producción desde pequeñas plantas que usen procesos discontinuos hasta grandes plantas de procesado continuo.En primer lugar, esta tesis trata la gestión de los procesos continuos en los que suelen fabricar productos muy similares a gran escala. La gran ventaja de los procesos continuos es que pueden conseguir mayor consistencia en la calidad de los productos y que pueden aprovechar las economías de escala que reducen los costes y residuos. Sin embargo, la industria química para mantenerse competitiva necesita adaptar continuamente sus procesos a las condiciones del mercado y de operación. El sistema de control supervisor presentado en esta parte de la tesis disminuye el tiempo de reacción frente a incidentes en los procesos continuos y re-optimiza la producción en tiempo real, si existe posibilidad de mejora.A continuación, esta tesis trata la gestión de los procesos semicontinuos que permiten una operación más flexible y personalizada. Los procesos semicontinuos operan con puestas en marcha y paradas periódicas para acomodar las frecuentes transiciones entre diferentes productos. Esta tesis presenta un nuevo concepto de fabricación flexible que permite programar perfiles variables de velocidad de producción dentro de cada campaña de producción.La mayor parte del trabajo de investigación de esta tesis se dedica a la planificación de la producción en los procesos discontinuos por lotes, utilizados principalmente en la producción de productos químicos con alto valor añadido. Estos procesos ofrecen varias ventajas respecto a los procesos continuos y semicontinuos debido a la mayor flexibilidad para acomodar diversos productos, diferentes capacidades de producción, y la posibilidad de realizar operaciones completamente diferentes en los mismos equipos. Sin embargo, la obtención del plan de producción óptimo usando se complica al aumentar la complejidad de la planta y/o el número de lotes a planificar. La simplificación de considerar tiempos de transferencia despreciables es generalmente aceptada en la literatura para evitar la complejidad del manejo de las operaciones de transferencia. En cambio, esta tesis pretende resaltar el papel crítico que juegan las operaciones de transferencia en la sincronización de tareas, y en la consiguiente determinación de planes de producción factibles.Siguiendo con los procesos por lotes, esta tesis demuestra que el uso del concepto de recetas flexibles mejora la operación de los procesos en ambientes de producción con mucha incertidumbre. La flexibilidad de las receta se considera como una oportunidad adicional, tanto para la planificación de la producción reactiva como preactiva, reduciendo el riesgo de llegar a resultados económicamente desfavorables.Finalmente, esta tesis presenta las plantas discontinuas sin tuberías como una alternativas a las plantas por lotes clásicas. En la búsqueda de formas más competitivas y efectivas de producción, la flexibilidad para producir un elevado número de productos en plantas por lotes es limitada debido a la necesidad de equipos fijos conectados por tuberías y frecuentes tareas de limpieza. Las plantas sin tuberías presentan una mayor flexibilidad ya que el material se transfiere entre estaciones de procesamiento usando equipos que se mueven dentro de la planta. El trabajo presentado en esta parte de la tesis contribuye a la mejora en la gestión de este tipo de plantas proponiendo una formulación más eficiente a las encontradas en la literatura que resuelve el problema de la planificación de la producción.En resumen, esta tesis desarrolla nuevas estrategias de modelado y métodos de resolución encaminados al soporte de la toma de decisiones que explotan la flexibilidad intrínseca de los procesos químicos. Las principales ventajas de cada una de las contribuciones de esta tesis se demuestran mediante su aplicación a diferentes casos de estudio. / The chemical industry has become increasingly competitive over the past decades. Companies are required to adapt to changing market conditions and meet stricter product specifications. While globalization has opened new markets for the chemical industry, it has also increased the competitor pool, giving an advantage to companies with more efficient and highly integrated plants.In this context, the main aim of this thesis is to demonstrate new concepts and computational methods that exploit process flexibility to enhance plant profitability under transient operating conditions. These methods ensure that safety and product quality requirements are consistently met. This thesis makes contributions to the optimization and management of production in plants ranging from small batch plants to large capacity continuous processes.First, this thesis addresses the management of continuous processes, in which similar products are mass produced. Continuous processes can achieve the highest consistency and product quality by taking advantage of economies of scale and reduced manufacturing costs and waste. However, in order to remain competitive in the market, plants are required to dynamically adapt their processes to fit the continuously changing market and operating conditions. The supervisory control system presented in this part of the thesis decreases the system reaction time to incidences and re-optimizes the production in real time if the opportunity for improved performance exists.Next, this thesis addresses the management of semicontinuous processes, which allow more customized and flexible operation. Semicontinuous processes run with periodic start-ups and shutdowns to accommodate frequent product transitions. This thesis proposes an optimization model that creates improved production schedules by introducing a new concept of flexible manufacturing that allows production rate profiles to be programmed within each operation campaign.The major part of the research work of this thesis deals with the operational management of batch processes, which are mainly used for the production of high value-added chemicals. Batch processing offers the advantage of increased flexibility in product variety, production volume, and the assortment of operations that can be processed by a particular piece of equipment. However, the trade-off is that production scheduling is significantly complicated by the large number of batches involved with different production paths. In order to avoid the complexity of managing transfer operations, the assumption of negligible transfer times is generally accepted in batch scheduling. Conversely, this thesis highlights the critical role that transfer operations play in the synchronization of tasks and in determining the feasibility of production schedules.Continuing to focus on batch plant operation, this thesis demonstrates that the use of the concept of flexible recipes enhances the operation batch plants within an uncertain environment. Recipe flexibility is considered as an additional opportunity for reactive scheduling as well as a proactive way to reduce the risk of meeting unfavorable scenarios.Finally, this thesis examines pipeless plants as an alternative to batch plants. In the search for more competitive and effective ways of production, flexibility of batch plants for producing a large number of products is limited due to the need for equipment, piping and frequent cleaning tasks. Pipeless plants have enhanced flexibility over batch plants, because the material is moved along its production path through moveable vessels. This part of the thesis contributes to the optimization of the management of pipeless plants by proposing an alternative formulation for solving short-term scheduling problems.In summary, this thesis provides novel modeling approaches and solution methods aimed at supporting the decision-making process in plant production scheduling which exploit the existing flexibility in chemical processes. The main advantages of each contribution are highlighted through case studies.

Process control and monitoring is a common problem in high value added chemical manufacturing industries where batch processes are used to produce wide range of products on the same piece of equipment. This results in frequent adjustments on control and monitoring schemes. A chemical toner manufacturing process is representative of an industrial case which is used in this thesis. Process control and monitoring problem of batch processes have been researched, mostly through the simulation, and published in the past . However, the concept of applying the subject to chemical toner manufacturing process or to use a single indicator for multiple pieces of equipment have never been visited previously. In the case study of this research, there are many different factors that may affect the final quality of the products including reactor batch temperature, jacket temperature, impeller speed, rate of the addition of material to the reactor, or process variable associated with the pre-weight tank. One of the challenging tasks for engineers is monitoring of these process variables and to make necessary adjustments during the progression of a batch and change controls strategy of future batches upon completion of an existing batch. Another objective of the proposed research is the establishment of the operational boundaries to monitor the process through the usage of process trajectories of the history of the past successful batches. In this research, process measurements and product quality values of the past successful batches were collected and projected into matrix of data; and preprocessed through time alignment, centering, and scaling. Then the preprocessed data was projected into lower dimensions (latent variables) to produce latent variables and their trajectories during successful batches. Following the identification of latent variables, an empirical model was built through a 4-fold cross validation that can represent the operation of a successful batch. The behavior of two abnormal batches, batch 517 and 629, is then compared to the model by testing its statistical properties. Once the abnormal batches were flagged, their data set were folded back to original dimension to form a localization path for the time of abnormality and process variables that contributed to the abnormality. In each case the process measurement were used to establish operational boundaries on the latent variable space.

No description available.

Process control and monitoring is a common problem in high value added chemical manufacturing industries where batch processes are used to produce wide range of products on the same piece of equipment. This results in frequent adjustments on control and monitoring schemes. A chemical toner manufacturing process is representative of an industrial case which is used in this thesis. Process control and monitoring problem of batch processes have been researched, mostly through the simulation, and published in the past . However, the concept of applying the subject to chemical toner manufacturing process or to use a single indicator for multiple pieces of equipment have never been visited previously. In the case study of this research, there are many different factors that may affect the final quality of the products including reactor batch temperature, jacket temperature, impeller speed, rate of the addition of material to the reactor, or process variable associated with the pre-weight tank. One of the challenging tasks for engineers is monitoring of these process variables and to make necessary adjustments during the progression of a batch and change controls strategy of future batches upon completion of an existing batch. Another objective of the proposed research is the establishment of the operational boundaries to monitor the process through the usage of process trajectories of the history of the past successful batches. In this research, process measurements and product quality values of the past successful batches were collected and projected into matrix of data; and preprocessed through time alignment, centering, and scaling. Then the preprocessed data was projected into lower dimensions (latent variables) to produce latent variables and their trajectories during successful batches. Following the identification of latent variables, an empirical model was built through a 4-fold cross validation that can represent the operation of a successful batch. The behavior of two abnormal batches, batch 517 and 629, is then compared to the model by testing its statistical properties. Once the abnormal batches were flagged, their data set were folded back to original dimension to form a localization path for the time of abnormality and process variables that contributed to the abnormality. In each case the process measurement were used to establish operational boundaries on the latent variable space.

Processos industriais que ocorrem em bateladas são empregados com freqüência na produção de alguns itens. Tais processos disponibilizam uma estrutura de dados bastante peculiar e, diante disso, existe um crescente interesse no desenvolvimento de cartas de controle multivariadas mais apropriadas para seu monitoramento. Destaca-se aqui uma abordagem recente que utiliza cartas de controle baseadas no método Statis. O Statis constitui-se numa técnica exploratória que permite avaliar similaridade entre matrizes de dados. Entretanto, esta técnica avalia a similaridade no contexto linear, isto é, investiga estruturas de correlação lineares nos dados. Propõe-se nesta tese a utilização de cartas de controle baseadas no Statis em conjunto com um kernel para monitoramento de processos com presença de nãolinearidades fortes. Através dos kernels, definem-se funções não lineares dos dados para melhor representação da estrutura a ser caracterizada pelo método Statis. Esta nova abordagem, denominada Kernel-Statis, é desenvolvida e avaliada utilizando dados de um processo simulado. / Industrial batch processes are widely used in the production of some items. Such processes provide a peculiar data structure; therefore, there is a growing interest in the development of customized multivariate control charts for their monitoring. We investigate a recent approach that uses control charts based on the Statis method. Statis is an exploratory technique for measuring similarities between data matrices. However, the technique only assesses similarities in a linear context, i.e. investigating structures of linear correlation in the data. In this thesis we propose control charts based on the Statis method in conjunction with a kernel for monitoring processes in the presence of strong non-linearities. Through the kernels we define non-linear functions of data for better representing the structure to be characterized by the Statis method. The new approach, named Kernel-Statis, is developed and illustrated using simulated data.

Processos industriais que ocorrem em bateladas são empregados com freqüência na produção de alguns itens. Tais processos disponibilizam uma estrutura de dados bastante peculiar e, diante disso, existe um crescente interesse no desenvolvimento de cartas de controle multivariadas mais apropriadas para seu monitoramento. Destaca-se aqui uma abordagem recente que utiliza cartas de controle baseadas no método Statis. O Statis constitui-se numa técnica exploratória que permite avaliar similaridade entre matrizes de dados. Entretanto, esta técnica avalia a similaridade no contexto linear, isto é, investiga estruturas de correlação lineares nos dados. Propõe-se nesta tese a utilização de cartas de controle baseadas no Statis em conjunto com um kernel para monitoramento de processos com presença de nãolinearidades fortes. Através dos kernels, definem-se funções não lineares dos dados para melhor representação da estrutura a ser caracterizada pelo método Statis. Esta nova abordagem, denominada Kernel-Statis, é desenvolvida e avaliada utilizando dados de um processo simulado. / Industrial batch processes are widely used in the production of some items. Such processes provide a peculiar data structure; therefore, there is a growing interest in the development of customized multivariate control charts for their monitoring. We investigate a recent approach that uses control charts based on the Statis method. Statis is an exploratory technique for measuring similarities between data matrices. However, the technique only assesses similarities in a linear context, i.e. investigating structures of linear correlation in the data. In this thesis we propose control charts based on the Statis method in conjunction with a kernel for monitoring processes in the presence of strong non-linearities. Through the kernels we define non-linear functions of data for better representing the structure to be characterized by the Statis method. The new approach, named Kernel-Statis, is developed and illustrated using simulated data.

Processos industriais que ocorrem em bateladas são empregados com freqüência na produção de alguns itens. Tais processos disponibilizam uma estrutura de dados bastante peculiar e, diante disso, existe um crescente interesse no desenvolvimento de cartas de controle multivariadas mais apropriadas para seu monitoramento. Destaca-se aqui uma abordagem recente que utiliza cartas de controle baseadas no método Statis. O Statis constitui-se numa técnica exploratória que permite avaliar similaridade entre matrizes de dados. Entretanto, esta técnica avalia a similaridade no contexto linear, isto é, investiga estruturas de correlação lineares nos dados. Propõe-se nesta tese a utilização de cartas de controle baseadas no Statis em conjunto com um kernel para monitoramento de processos com presença de nãolinearidades fortes. Através dos kernels, definem-se funções não lineares dos dados para melhor representação da estrutura a ser caracterizada pelo método Statis. Esta nova abordagem, denominada Kernel-Statis, é desenvolvida e avaliada utilizando dados de um processo simulado. / Industrial batch processes are widely used in the production of some items. Such processes provide a peculiar data structure; therefore, there is a growing interest in the development of customized multivariate control charts for their monitoring. We investigate a recent approach that uses control charts based on the Statis method. Statis is an exploratory technique for measuring similarities between data matrices. However, the technique only assesses similarities in a linear context, i.e. investigating structures of linear correlation in the data. In this thesis we propose control charts based on the Statis method in conjunction with a kernel for monitoring processes in the presence of strong non-linearities. Through the kernels we define non-linear functions of data for better representing the structure to be characterized by the Statis method. The new approach, named Kernel-Statis, is developed and illustrated using simulated data.

[EN] This thesis is aimed to study the implications of the statistical modeling approaches proposed for the bilinear modeling of batch processes, develop new techniques to overcome some of the problems that have not been yet solved and apply them to data of biochemical processes. The study, discussion and development of the new methods revolve around the four steps of the modeling cycle, from the alignment, preprocessing and calibration of batch data to the monitoring of batches trajectories. Special attention is given to the problem of the batch synchronization, and its effect on the modeling from different angles. The manuscript has been divided into four blocks. First, a state-of- the-art of the latent structures based-models in continuous and batch processes and traditional univariate and multivariate statistical process control systems is carried out. The second block of the thesis is devoted to the preprocessing of batch data, in particular, to the equalization and synchronization of batch trajectories. The first section addresses the problem of the lack of equalization in the variable trajectories. The different types of unequalization scenarios that practitioners might finnd in batch processes are discussed and the solutions to equalize batch data are introduced. In the second section, a theoretical study of the nature of batch processes and of the synchronization of batch trajectories as a prior step to bilinear modeling is carried out. The topics under discussion are i) whether the same synchronization approach must be applied to batch data in presence of different types of asynchronisms, and ii) whether synchronization is always required even though the length of the variable trajectories are constant across batches. To answer these questions, a thorough study of the most common types of asynchronisms that may be found in batch data is done. Furthermore, two new synchronization techniques are proposed to solve the current problems in post-batch and real-time synchronization. To improve fault detection and classification, new unsupervised control charts and supervised fault classifiers based on the information generated by the batch synchronization are also proposed. In the third block of the manuscript, a research work is performed on the parameter stability associated with the most used synchronization methods and principal component analysis (PCA)-based Batch Multivariate Statistical Process Control methods. The results of this study have revealed that accuracy in batch synchronization has a profound impact on the PCA model parameters stability. Also, the parameter stability is closely related to the type of preprocessing performed in batch data, and the type of model and unfolding used to transform the three-way data structure to two-way. The setting of the parameter stability, the source of variability remaining after preprocessing and the process dynamics should be balanced in such a way that multivariate statistical models are accurate in fault detection and diagnosis and/or in online prediction. Finally, the fourth block introduces a graphical user-friendly interface developed in Matlab code for batch process understanding and monitoring. To perform multivariate analysis, the last developments in process chemometrics, including the methods proposed in this thesis, are implemented. / [ES] La presente tesis doctoral tiene como objetivo estudiar las implicaciones de los métodos estadísticos propuestos para la modelización bilineal de procesos por lotes, el desarrollo de nuevas técnicas para solucionar algunos de los problemas más complejos aún por resolver en esta línea de investigación y aplicar los nuevos métodos a datos provenientes de procesos bioquímicos para su evaluación estadística. El estudio, la discusión y el desarrollo de los nuevos métodos giran en torno a las cuatro fases del ciclo de modelización: desde la sincronización, ecualización, preprocesamiento y calibración de los datos, a la monitorización de las trayectorias de las variables del proceso. Se presta especial atención al problema de la sincronización y su efecto en la modelización estadística desde distintas perspectivas. El manuscrito se ha dividido en cuatro grandes bloques. En primer lugar, se realiza una revisión bibliográfica de las técnicas de proyección sobre estructuras latentes para su aplicación en procesos continuos y por lotes, y del diseño de sistemas de control basados en modelos estadísticos multivariantes. El segundo bloque del documento versa sobre el preprocesamiento de los datos, en concreto, sobre la ecualización y la sincronización. La primera parte aborda el problema de la falta de ecualización en las trayectorias de las variables. Se discuten las diferentes políticas de muestreo que se pueden encontrar en procesos por lotes y las soluciones para ecualizar las variables. En la segunda parte de esta sección, se realiza un estudio teórico sobre la naturaleza de los procesos por lotes y de la sincronización de las trayectorias como paso previo a la modelización bilineal. Los temas bajo discusión son: i) si se debe utilizar el mismo enfoque de sincronización en lotes afectados por diferentes tipos de asincronismos, y ii) si la sincronización es siempre necesaria aún y cuando las trayectorias de las variables tienen la misma duración en todos los lotes. Para responder a estas preguntas, se lleva a cabo un estudio exhaustivo de los tipos más comunes de asincronismos que se pueden encontrar en este tipo de datos. Además, se proponen dos nuevas técnicas de sincronización para resolver los problemas existentes en aplicaciones post-morten y en tiempo real. Para mejorar la detección de fallos y la clasificación, también se proponen nuevos gráficos de control no supervisados y clasificadores de fallos supervisados en base a la información generada por la sincronización de los lotes. En el tercer bloque del manuscrito se realiza un estudio de la estabilidad de los parámetros asociados a los métodos de sincronización y a los métodos estadístico multivariante basados en el Análisis de Componentes Principales (PCA) más utilizados para el control de procesos. Los resultados de este estudio revelan que la precisión de la sincronización de las trayectorias tiene un impacto significativo en la estabilidad de los parámetros de los modelos PCA. Además, la estabilidad paramétrica está estrechamente relacionada con el tipo de preprocesamiento realizado en los datos de los lotes, el tipo de modelo a justado y el despliegue utilizado para transformar la estructura de datos de tres a dos dimensiones. El ajuste de la estabilidad de los parámetros, la fuente de variabilidad que queda después del preprocesamiento de los datos y la captura de las dinámicas del proceso deben ser a justados de forma equilibrada de tal manera que los modelos estadísticos multivariantes sean precisos en la detección y diagnóstico de fallos y/o en la predicción en tiempo real. Por último, el cuarto bloque del documento describe una interfaz gráfica de usuario que se ha desarrollado en código Matlab para la comprensión y la supervisión de procesos por lotes. Para llevar a cabo los análisis multivariantes, se han implementado los últimos desarrollos en la quimiometría de proc / [CA] Aquesta tesi doctoral te com a objectiu estudiar les implicacions dels mètodes de modelització estadística proposats per a la modelització bilineal de processos per lots, el desenvolupament de noves tècniques per resoldre els problemes encara no resolts en aquesta línia de recerca i aplicar els nous mètodes a les dades dels processos bioquímics. L'estudi, la discussió i el desenvolupament dels nous mètodes giren entorn a les quatre fases del cicle de modelització, des de l'alineació, preprocessament i el calibratge de les dades provinents de lots, a la monitorització de les trajectòries. Es presta especial atenció al problema de la sincronització per lots, i el seu efecte sobre el modelatge des de diferents angles. El manuscrit s'ha dividit en quatre grans blocs. En primer lloc, es realitza una revisió bibliogràfica dels principals mètodes basats en tècniques de projecció sobre estructures latents en processos continus i per lots, així com dels sistemes de control estadístics multivariats. El segon bloc del document es dedica a la preprocessament de les dades provinents de lots, en particular, l' equalització i la sincronització. La primera part aborda el problema de la manca d'equalització en les trajectòries de les variables. Es discuteixen els diferents tipus d'escenaris en que les variables estan mesurades a distints intervals i les solucions per equalitzar-les en processos per lots. A la segona part d'aquesta secció es porta a terme un estudi teòric de la naturalesa dels processos per lots i de la sincronització de les trajectòries de lots com a pas previ al modelatge bilineal. Els temes en discussió són: i) si el mateix enfocament de sincronització ha de ser aplicat a les dades del lot en presència de diferents tipus de asincronismes, i ii) si la sincronització sempre es requereix tot i que la longitud de les trajectòries de les variables són constants en tots el lots. Per respondre a aquestes preguntes, es du a terme un estudi exhaustiu dels tipus més comuns de asincronismes que es poden trobar en les dades provinents de lots. A més, es proposen dues noves tècniques de sincronització per resoldre els problemes existents la sincronització post-morten i en temps real. Per millorar la detecció i la classificació de anomalies, també es proposen nous gràfics de control no supervisats i classificadors de falla supervisats dissenyats en base a la informació generada per la sincronització de lots. En el tercer bloc del manuscrit es realitza un treball de recerca sobre l'estabilitat dels paràmetres associats als mètodes de sincronització i als mètodes estadístics multivariats basats en l'Anàlisi de Components Principals (PCA) més utilitzats per al control de processos. Els resultats d'aquest estudi revelen que la precisió en la sincronització per lots te un profund impacte en l'estabilitat dels paràmetres dels models PCA. A més, l'estabilitat paramètrica està estretament relacionat amb el tipus de preprocessament realitzat en les dades provinents de lots, el tipus de model i el desplegament utilitzat per transformar l'estructura de dades de tres a dos dimensions. L'ajust de l'estabilitat dels paràmetres, la font de variabilitat que queda després del preprocessament i la captura de la dinàmica de procés ha de ser equilibrada de tal manera que els models estadístics multivariats són precisos en la detecció i diagnòstic de fallades i/o en la predicció en línia. Finalment, el quart bloc del document introdueix una interfície gràfica d'usuari que s'ha dissenyat e implementat en Matlab per a la comprensió i la supervisió de processos per lots. Per dur a terme aquestes anàlisis multivariats, s'han implementat els últims desenvolupaments en la quimiometria de processos, incloent-hi els mètodes proposats en aquesta tesi. / González Martínez, JM. (2015). ADVANCES ON BILINEAR MODELING OF BIOCHEMICAL BATCH PROCESSES [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/55684 / TESIS / Premios Extraordinarios de tesis doctorales

This Master's thesis focuses on improving the understanding and monitoring of the Hot Isostatic Pressing (HIP) sintering process used by Seco Tools AB to manufacture cemented carbides for cutting tools. While essential for producing cutting tools with superior hardness and toughness the HIP sintering process introduces a complex relationship between the selected process parameters and the achieved materials properties. With the goal of establishing batch process monitoring capabilities, this master thesis employs Multivariate Statistical Process Control (MSPC) strategies through the creation of Batch Evolution Models (BEMs) and Batch Level Models (BLMs) to monitor, predict end-product quality, and analyze the batch production HIP sintering process.  The developed models effectively account for significant variation in the HIP sintering process and demonstrate potential in identifying deviant batches. Enhancements to the models' performance are achieved through the incorporation of preprocessing, phase-specific variable selection, and specialized model training. These proposed enhancements yield discernible improvements, as evidenced by enhanced model fit and other statistical metrics.  Challenges arise when the models are tested with real-time data due to progressive changes in some tracked process variables. Block-scaling is applied to restore the real-time monitoring capabilities, but also introduces additional complexity to the models. In addition, this master thesis highlights the need for continuous and regular maintenance of these models to ensure real-time monitoring and anomaly detection capabilities. The models demonstrate varied effectiveness in predicting final product quality. For instance, they exhibit some potential in predicting Magnetic Saturation (MS), but their ability to predict Magnetic Coercivity (HC) seems nonexistent. Despite attempts to improve the predictive abilities the models are still not able to confidently predict these metrics. The master’s thesis highlights variability in powder contents and access to data of known quality nonconformities as potential areas for improving the predictive models.