Relevant bibliographies by topics / Process control Simulation methods

Academic literature on the topic 'Process control Simulation methods'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Process control Simulation methods"

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Pugh, G. Allen. "The evaluation of statistical process control methods by simulation." Computers & Industrial Engineering 15, no. 1-4 (January 1988): 360–63. http://dx.doi.org/10.1016/0360-8352(88)90112-x.

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Edgeman, Rick L., and David Drain. "Statistical Methods for Industrial Process Control." Technometrics 40, no. 2 (May 1998): 154. http://dx.doi.org/10.2307/1270649.

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Poteriailo, L. O., V. V. Protsjuk, and K. I. Kravtsiv. "KNOWLEDGE-ORIENTED DECISION-MAKING METHODS IN SIMULATIONS OF TECHNOLOGICAL PROCESS SIMULATION." METHODS AND DEVICES OF QUALITY CONTROL, no. 2(45) (December 28, 2020): 132–45. http://dx.doi.org/10.31471/1993-9981-2020-2(45)-132-145.

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The article presents the results of research in the field of simulation of drilling processes using modern computer modeling. The main parameters of the drilling process are determined as theoretical considerations aimed at introducing concepts related to simulation modeling and computer modeling in drilling. The analysis of the models used in the simulation of drilling processes is carried out. The basic characteristics of the simulator modeling are highlighted, which provides a holistic perception of technological processes, as well as any degree of their detailing. The main methods of modeling used in the development of automated control systems and simulators of industrial installations, ways of developing their software and some aspects of creating effective software and computer systems are presented. Further, a review of the essence of technological simulators is carried out, from a technical point of view, the current state of training systems for training operators of technological processes is highlighted. The differences between simulators and other teaching aids and the specifics of simulators for technical processes are presented. The characteristic features and prospects of simulator building in various industries are briefly described. The compulsory components of the simulators and the quality criteria of the simulators are determined. A study of the existing technical solutions for systems of the "Drilling simulators" class was carried out. Conclusions are made regarding the practical aspects of using modern engineering solutions for drilling simulators. The advantages are determined as a result of using simulators in various types of operational-tactical exercises, as the main form of improving the optimization of drilling control both for production tasks and training tasks. Particular emphasis is placed on the Drillsimm5000 simulator, which is used in the training of drilling specialists at the Ivano-Frankivsk Technical National University of Oil and Gas. From the standpoint of various services of the enterprise interested in purchasing simulators, the potential benefits of computer training and the tasks that need to be solved for the successful implementation of simulators are analyzed, problems associated with their implementation are presented.
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Zhang, Xiao Zhong, Fan Qin Meng, and Jie Hui Wang. "Optimizing Control Methods of Airport Pipeline Refueling Process." Applied Mechanics and Materials 738-739 (March 2015): 1007–11. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.1007.

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Due to the non-linearity and long delay of airport pipe line refueling system, it is difficult for classical control methods to ensure stable pumping pressure and refueling flow. To improve the stability of the refueling process, the paper introduces human-simulated intelligent control (HSIC) method to the recognization of refueling status, online self-adjusting and control of refueling parameters. Simulation shows that the stability and accuracy of HSIC control methods were better than that of classical PID and fuzzy PID control.
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Şipoș, Anca, and Mariana Liliana Păcală. "Teaching process control in food engineering: dynamic simulation of a fermentation control process." Balkan Region Conference on Engineering and Business Education 2, no. 1 (December 20, 2017): 313–19. http://dx.doi.org/10.1515/cplbu-2017-0041.

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Abstract Students usually have difficulties to understand abstract concepts of process control. Implementing in teaching process the inquiry-based learning helps students to follow methods and practices similar to those of professional scientists in order to construct knowledge. The paper describes the steps reached in simulation-based learning: from experimental data obtained by the students in their practical method (study and measurement of variables to some fermentation processes) to the simulated the behaviour of the process under a feedback control system. By providing opportunities for students to check their understanding and reflect on their learning process performance is enhanced over a traditional lecture course.
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Zhao, Wei, Yu Liang Chen, and Wen Juan Huang. "Research of Intelligent Control Methods for Hot Strip’s Coiling Temperature." Key Engineering Materials 439-440 (June 2010): 236–40. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.236.

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This paper briefly describes the importance of coiling temperature control in the strip production process, and analysis which shows that the current existence of coiling temperature control is difficult, for the laminar cooling process is one with a strong non-linear, distributed parameter, time-varying. Intelligent control method is presented and carried out with the Matlab simulation. The simulation result shows that this method will enable the ultimate precision of coiling temperature control within 5 °C.
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Feng, Shao Wei, Jing Zhang, and Shao Chun Ding. "Simulation Analysis of Production Control Methods in Manufacturing Systems." Advanced Materials Research 490-495 (March 2012): 1704–8. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.1704.

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It is very important to improve shop production performance in manufacturing process. The main manufacturing management methods include Kanban and Drum Buffer Rope (DBR) systems. In this paper computer simulation is used to evaluate the performance of these manufacturing systems. A simulation model was developed to collect and analyze some key performance indexes including total system output, flow time and average WIP invention. The optimal buffer size was found out by studying the two manufacturing systems at different capacities. The systems were also compared with and without machine breakdowns. The simulation model provided a significant insight into the two systems and the benefits of both the systems were realized
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Parulski, Paweł, Patryk Bartkowiak, and Dariusz Pazderski. "Evaluation of Linearization Methods for Control of the Pendubot." Applied Sciences 11, no. 16 (August 19, 2021): 7615. http://dx.doi.org/10.3390/app11167615.

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The aim of this paper is to test the usefulness of a new approach based on partial feedback linearization to control the Pendubot. The control problem stated in the article is to stabilize the Pendubot in the upright position. In particular, properties of the closed-loop system and the zero dynamics are investigated and illustrated by results of simulations. Next, the performance of a hybrid-like controller in the case of input saturation is evaluated by conduction extensive simulation trails. The experimental results suggest that the considered control methodology can be successfully applied for a real system.
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Zhao, Zhiqiang, and Feiyue Zhou. "Optimal Control Methods of Experiment Times in System-of-Systems Combat Computer Simulation." ITM Web of Conferences 26 (2019): 03004. http://dx.doi.org/10.1051/itmconf/20192603004.

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In the process of scheme optimization, in order to eliminate the influence of random factor, it needs to conduct computer simulation of Monte Carlo. Therefore, it is proposed to introduce confidence interval into systemof-systems combat simulation, and confirm whether the Monte Carlo simulation finishes according to data sample generated in simulation process. According to characteristic of data sample, extend correspondingly confidence interval method, and under the condition of obtaining the solution meeting accuracy requirements, reduce simulation experiment times as far as possible. The simulation experiment results show that confidence interval extension method is able to possess self-adaptation control to Monte Carlo simulation.
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Wang, Jie-sheng, Na-na Shen, and Shi-feng Sun. "Integrated Modeling and Intelligent Control Methods of Grinding Process." Mathematical Problems in Engineering 2013 (2013): 1–15. http://dx.doi.org/10.1155/2013/456873.

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The grinding process is a typical complex nonlinear multivariable process with strongly coupling and large time delays. Based on the data-driven modeling theory, the integrated modeling and intelligent control method of grinding process is carried out in the paper, which includes the soft-sensor model of economic and technique indexes, the optimized set-point model utilizing case-based reasoning, and the self-tuning PID decoupling controller. For forecasting the key technology indicators (grinding granularity and mill discharge rate of grinding process), an adaptive soft-sensor modeling method based on wavelet neural network optimized by the improved shuffled frog leaping algorithm (ISFLA) is proposed. Then, a set point optimization control strategy of grinding process based on case-based reasoning (CBR) method is adopted to obtain the optimized velocity set-point of ore feed and pump water feed in the grinding process controlled loops. Finally, a self-tuning PID decoupling controller optimized is used to control the grinding process. Simulation results and industrial application experiments clearly show the feasibility and effectiveness of control methods and satisfy the real-time control requirements of the grinding process.
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Dissertations / Theses on the topic "Process control Simulation methods"

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Capaci, Francesca. "Contributions to the Use of Statistical Methods for Improving Continuous Production." Licentiate thesis, Luleå tekniska universitet, Industriell Ekonomi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-66256.

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Complexity of production processes, high computing capabilities, and massive datasets characterize today’s manufacturing environments, such as those of continuous andbatch production industries. Continuous production has spread gradually acrossdifferent industries, covering a significant part of today’s production. Commonconsumer goods such as food, drugs, and cosmetics, and industrial goods such as iron,chemicals, oil, and ore come from continuous processes. To stay competitive intoday’s market requires constant process improvements in terms of both effectivenessand efficiency. Statistical process control (SPC) and design of experiments (DoE)techniques can play an important role in this improvement strategy. SPC attempts toreduce process variation by eliminating assignable causes, while DoE is used toimprove products and processes by systematic experimentation and analysis. However,special issues emerge when applying these methods in continuous process settings.Highly automated and computerized processes provide an exorbitant amount ofserially dependent and cross-correlated data, which may be difficult to analyzesimultaneously. Time series data, transition times, and closed-loop operation areexamples of additional challenges that the analyst faces.The overall objective of this thesis is to contribute to using of statisticalmethods, namely SPC and DoE methods, to improve continuous production.Specifically, this research serves two aims: [1] to explore, identify, and outlinepotential challenges when applying SPC and DoE in continuous processes, and [2] topropose simulation tools and new or adapted methods to overcome the identifiedchallenges.The results are summarized in three appended papers. Through a literaturereview, Paper A outlines SPC and DoE implementation challenges for managers,researchers, and practitioners. For example, problems due to process transitions, themultivariate nature of data, serial correlation, and the presence of engineering processcontrol (EPC) are discussed. Paper B further explores one of the DoE challengesidentified in Paper A. Specifically, Paper B describes issues and potential strategieswhen designing and analyzing experiments in processes operating under closed-loopcontrol. Two simulated examples in the Tennessee Eastman (TE) process simulatorshow the benefits of using DoE techniques to improve and optimize such industrialprocesses. Finally, Paper C provides guidelines, using flow charts, on how to use thecontinuous process simulator, “The revised TE process simulator,” run with adecentralized control strategy as a test bed for developing SPC and DoE methods incontinuous processes. Simulated SPC and DoE examples are also discussed.
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Scullin, Michelle E. "Integrating Value Stream Mapping and Simulation." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd898.pdf.

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Appell, Kenneth William. "A mathematical simulation of ETS' limestone emission control process using the method of characteristics fixed-bed configuration/gas-phase mass transport control." Ohio : Ohio University, 1989. http://www.ohiolink.edu/etd/view.cgi?ohiou1182276120.

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Propes, Nicholas Chung. "Hybrid Systems Diagnosis and Control Reconfiguration for Manufacturing Systems." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5150.

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A methodology for representing and analyzing manufacturing systems in a hybrid systems framework for control reconfiguration purposes in the presence of defects and failures at the product and system levels is presented. At the top level, a supervisory Petri net directs parts/jobs through the manufacturing system. An object-based hybrid systems model that incorporates both Petri nets at the event-driven level and differential equations at the time-driven level describes the subsystems. Rerouting capabilities utilizing this model at the product and operation levels were explained. Simulations were performed on a testbed model for optimal time and mode transition cost to determine the route for parts. The product level reconfiguration architecture utilizes an adaptive network-based fuzzy inference system (ANFIS) to map histogram comparison metrics to set-point adjustments when product defects were detected. Tests were performed on good and defective plastic parts from a plastic injection molding machine. In addition, a mode identification architecture was described that incorporates both time- and event-driven information to determine the operating mode of a system from measured sensor signals. Simulated data representing the measured process signals from a Navy ship chiller system were used to verify that the appropriate operating modes were detected.
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Sanchez, Urbina Israel. "Optimizing flow of plastic PBT with 45% glass and mineral fiber reinforcement in an injection over mold process using Taguchi, CPk and mold flow simulation software approaches." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Robles, Martínez Ángel. "Modelling, simulation and control of the filtration process in a submerged anaerobic membrane bioreactor treating urban wastewater." Doctoral thesis, Editorial Universitat Politècnica de València, 2013. http://hdl.handle.net/10251/34102.

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El reactor anaerobio de membranas sumergidas (SAnMBR) está considerado como tecnología candidata para mejorar la sostenibilidad en el sector de la depuración de aguas residuales, ampliando la aplicabilidad de la biotecnología anaerobia al tratamiento de aguas residuales de baja carga (v.g. agua residual urbana) o a condiciones medioambientales extremas (v.g. bajas temperaturas de operación). Esta tecnología alternativa de tratamiento de aguas residuales es más sostenible que las tecnologías aerobias actuales ya que el agua residual se transforma en una fuente renovable de energía y nutrientes, proporcionando además un recurso de agua reutilizable. SAnMBR no sólo presenta las principales ventajas de los reactores de membranas (i.e. efluente de alta calidad, y pocas necesidades de espacio), sino que también presenta las principales ventajas de los procesos anaerobios. En este sentido, la tecnología SAnMBR presenta una baja producción de fangos debido a la baja tasa de crecimiento de los microorganismos implicados en la degradación de la materia orgánica, presenta una baja demanda energética debido a la ausencia de aireación, y permite la generación de metano, el cual representa una fuente de energía renovable que mejora el balance energético neto del sistema. Cabe destacar el potencial de recuperación de nutrientes del agua residual bien cuando el efluente es destinado a irrigación directamente, o bien cuando debe ser tratado previamente mediante tecnologías de recuperación de nutrientes. El objetivo principal de esta tesis doctoral es evaluar la viabilidad de la tecnología SAnMBR como núcleo en el tratamiento de aguas residuales urbanas a temperatura ambiente. Por lo tanto, esta tesis se centra en las siguientes tareas: (1) implementación, calibración y puesta en marcha del sistema de instrumentación, control y automatización requerido; (2) identificación de los parámetros de operación clave que afectan al proceso de filtración; (3) modelación y simulación del proceso de filtración; y (4) desarrollo de estrategias de control para la optimización del proceso de filtración minimizando los costes de operación. En este trabajo de investigación se propone un sistema de instrumentación, control y automatización para SAnMBR, el cual fue esencial para alcanzar un comportamiento adecuado y estable del sistema frente a posibles perturbaciones. El comportamiento de las membranas fue comparable a sistemas MBR aerobios a escala industrial. Tras más de dos años de operación ininterrumpida, no se detectaron problemas significativos asociados al ensuciamiento irreversible de las membranas, incluso operando a elevadas concentraciones de sólidos en el licor mezcla (valores de hasta 25 g·L-1 ). En este trabajo se presenta un modelo de filtración (basado en el modelo de resistencias en serie) que permitió simular de forma adecuada el proceso de filtración. Por otra parte, se propone un control supervisor basado en un sistema experto que consiguió reducir el consumo energético asociado a la limpieza física de las membranas, un bajo porcentaje de tiempo destinado a la limpieza física respecto al total de operación, y, en general, un menor coste operacional del proceso de filtración. Esta tesis doctoral está integrada en un proyecto nacional de investigación, subvencionado por el Ministerio de Ciencia e Innovación (MICINN), con título ¿Modelación de la aplicación de la tecnología de membranas para la valorización energética de la materia orgánica del agua residual y la minimización de los fangos producidos¿ (MICINN, proyecto CTM2008-06809- C02-01/02). Para obtener resultados representativos que puedan ser extrapolados a plantas reales, esta tesis doctoral se ha llevado a cabo utilizando un sistema SAnMBR que incorpora módulos comerciales de membrana de fibra hueca. Además, esta planta es alimentada con el efluente del pre-tratamiento de la EDAR del Barranco del Carraixet (Valencia, España).
Robles Martínez, Á. (2013). Modelling, simulation and control of the filtration process in a submerged anaerobic membrane bioreactor treating urban wastewater [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34102
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Chen, Shuai. "Investigation of FEM numerical simulation for the process of metal additive manufacturing in macro scale." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI048/document.

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La fabrication additive (FA) est devenue une nouvelle alternative pour la fabrication des pièces dans l'industrie. Cependant, il existe encore des limites pour ce procédé, en particulier la forme finale défavorable et les propriétés macroscopiques indésirables des pièces métalliques construites dans les systèmes de FA. La distorsion ou la fissure due à la contrainte résiduelle de ces pièces pose généralement de graves problèmes pour certains types de technologie de la FA métallique. Dans un système de FA, la qualité finale d'une pièce métallique dépend de nombreux paramètres de procédé, qui sont normalement optimisés par une série d'expériences sur des machines de FA. La simulation macroscopique dédiée au procédé de FA est une alternative potentielle pour les pièces métalliques fabriquées par la fabrication additive. Dans cette thèse, nous étudions d'abord le pré-processing de la simulation de FA par la méthode des éléments finis (FEM). Le procédé de fabrication additive est un phénomène multi-physique des champs couplés (champs thermique, mécanique et métallurgique). La simulation macroscopique est réalisée à deux niveaux différents. Au niveau de la couche, la reconstruction du modèle 3D est effectuée à partir du fichier de chemin de balayage de la machine de FA, basée sur la manipulation inverse de l'algorithme d'offsetting-clipping. Au niveau de la pièce, le modèle 3D de CAO est reconstruit dans un maillage des voxels, ce qui est pratique pour une pièce avec une géométrie complexe. Avec les températures de préchauffage différentes et les paramètres du procédé différents, la contrainte résiduelle d'une pièce est analysée. Ces simulations impliquent la technique potentielle pour réduire la contrainte résiduelle par l'optimisation des paramètres du procédé, au lieu de moyens traditionnels par augmenter la température de préchauffage. Basées sur la plateforme de simulation de FEM ci-dessus, deux simulations au niveau de ligne sont également étudiées dans cette thèse, visant à la relation entre le procédé de FA et la qualité finale de la pièce. Ces exemples démontrent la possibilité d'utiliser des simulations macroscopiques pour améliorer le contrôle de la qualité pendant le procédé de FA. Dans la première tâche, l'ensemble de données des paramètres de chauffage et la contrainte résiduelle sont générés par la simulation de FA. La corrélation entre eux est étudiée en utilisant des algorithmes de régression, tel que le réseau neuronal artificiel. Dans la deuxième tâche, un contrôleur de PID pour la boucle de rétroaction puissance-température est intégré dans la simulation de procédé de FA et l'auto-réglage de PID est numériquement étudié au lieu d'utiliser la machine de FA. Les deux tâches montrent le rôle important de la simulation de procédé macroscopique de FA, qui peut remplacer ou combiner les nombreuses expériences essai-erreur dans la fabrication additive métallique
Additive manufacturing (AM) has become a new option for the fabrication of metallic parts in industry. However, there are still some limitations for this application, especially the unfavourable final shape and undesired macroscopic properties of metallic parts built in AM systems. The distortion or crack due to the residual stress of these parts leads usually to severe problems for some kinds of metal AM technology. In an AM system, the final quality of a metallic part depends on many process parameters, which are normally optimized by a series of experiments on AM machines. In order to reduce the considerable time consumption and financial expense of AM experiments, the numerical simulation dedicated to AM process is a prospective alternative for metallic part fabricated by additive manufacturing. Because of the multi-scale character in AM process and the complex geometrical structures of parts, most of the academic researches in AM simulation concentrated on the microscopic melting pool. Consequently, the macroscopic simulation for the AM process of a metallic part becomes a current focus in this domain. In this thesis, we first study the pre-processing of AM simulation on Finite Element Method (FEM). The process of additive manufacturing is a multi-physics problem of coupled fields (thermal, mechanical, and metallurgical fields). The macroscopic simulation is conducted in two different levels with some special pre-processing work. For the layer level, the reconstruction of 3D model is conducted from the scan path file of AM machine, based on the inverse manipulation of offsetting-clipping algorithm. For the part level, the 3D model from CAD is reconstructed into a voxel-based mesh, which is convenient for a part with complex geometry. The residual stress of a part is analysed under different preheat temperatures and different process parameters. These simulations imply the potential technique of reducing residual stress by the optimisation of process parameters, instead of the traditional way by increasing preheat temperature. Based on the FEM simulation platform above, two simulations at line level are also studied in this thesis, aiming at the relation between the AM process and part's final quality. These examples demonstrate the feasibility of using macroscopic simulations to improve the quality control during the AM process. In the first task, dataset of heating parameters and residual stress are generated by AM simulation. The correlation between them is studied by using some regression algorithm, such as artificial neural network. In the second task, a PID controller for power-temperature feedback loop is integrated into AM process simulation and the PID auto-tuning is numerically investigated instead of using AM machine. Both of the two tasks show the important role of AM macroscopic process simulation, which may replace or combine with the numerous trial and error of experiments in metal additive manufacturing
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Pitra, Michal. "Adaptivní regulátory s principy umělé inteligence v prostředí MATLAB - B&R." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217708.

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The diploma thesis is focused on an adaptive control, especially in a self-tuning controller area. The thesis is divided into two main parts. The first part deals with identification methods of the adaptive control. The recursive least squares algorithm and the neural network method are the most popular identification methods. These methods are contrasted and the identification quality evaluation is done. The second part compares various types of the adaptive controllers with a non-adjustable PSD controller. The adaptive controllers are investigated from the various identification method point of view. The user graphic interface was realized for the identification and regulatory part. The time behavior of system responses after incoming disturbance and dynamic process changes during simulation systems control is compared with a physical model connected to B&R PLC. The comparison is done with the application of Matlab/Simulink program.
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Margulies, Mathias. "Contrôle optimal du procédé de cristallogenèse Bridgman vertical." Université Joseph Fourier (Grenoble), 1996. http://www.theses.fr/1996GRE10187.

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Le present travail a ete initie dans le cadre de l'optimisation d'une experience de tirage de cristaux de type bridgman vertical. Notre objectif est de mesurer l'apport potentiel de la mise en oeuvre de methodes numeriques d'optimisation. La qualite finale du cristal obtenu depend d'un grand nombre de parametres et de phenomenes physiques. Une etude bibliographique du travail de simulation existant pour la methode bridgman nous permet d'en isoler les plus influents et de proposer un modele simple pour notre etude. Nous nous fixons comme objectif de determiner un profil thermique de four et un profil de vitesse de tirage au cours du temps (parametres de tirage) tels que la derivee radiale de la temperature dans le materiau au cours de tout le tirage soit minimum (fonction cout) et sous certaines contraintes. Le champ de temperature est solution d'un probleme de stefan avec conditions aux limites de flux non lineaire. Nous donnons un resultat d'existence et d'unicite de la solution et etudions un algorithme semi-discret en temps permettant de resoudre la non-linearite des equations regissant le changement de phase. Le probleme de controle est ensuite etudie sous sa forme discrete en temps et en espace. Nous donnons les expressions des derivees partielles de la fonction cout et des contraintes par rapport aux parametres de controle en fonction de l'etat adjoint, ainsi qu'un resultat d'existence d'une solution au probleme de controle. Enfin, nous proposons une methode de descente pour resoudre le probleme de controle totalement discretise. Nous presentons les resultats obtenus dans une configuration particuliere, et en tirons les conclusions sur le fonctionnement de cette methode et les limites de notre modele.
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Paulson, Joel Anthony. "Modern control methods for chemical process systems." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/109672.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 301-322).
Strong trends in chemical engineering have led to increased complexity in plant design and operation, which has driven the demand for improved control techniques and methodologies. Improved control directly leads to smaller usage of resources, increased productivity, improved safety, and reduced pollution. Model predictive control (MPC) is the most advanced control technology widely practiced in industry. This technology, initially developed in the chemical engineering field in the 1970s, was a major advance over earlier multivariable control methods due to its ability to seamlessly handle constraints. However, limitations in industrial MPC technology spurred significant research over the past two to three decades in the search of increased capability. For these advancements to be widely implemented in industry, they must adequately address all of the issues associated with control design while meeting all of the control system requirements including: -- The controller must be insensitive to uncertainties including disturbances and unknown parameter values. -- The controlled system must perform well under input, actuator, and state constraints. -- The controller should be able to handle a large number of interacting variables efficiently as well as nonlinear process dynamics. -- The controlled system must be safe, reliable, and easy to maintain in the presence of system failures/faults. This thesis presents a framework for addressing these problems in a unified manner. Uncertainties and constraints are handled by extending current state-of-the-art MPC methods to handle probabilistic uncertainty descriptions for the unknown parameters and disturbances. Sensor and actuator failures (at the regulatory layer) are handled using a specific internal model control structure that allows for the regulatory control layer to perform optimally whenever one or more controllers is taken offline due to failures. Non-obvious faults, that may lead to catastrophic system failure if not detected early, are handled using a model-based active fault diagnosis method, which is also able to cope with constraints and uncertainties. These approaches are demonstrated on industrially relevant examples including crystallization and bioreactor processes.
by Joel Anthony Paulson.
Ph. D.
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Books on the topic "Process control Simulation methods"

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Ramirez, W. Fred. Computational methods for process simulation. 2nd ed. Oxford: Butterworths, 1997.

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Computational methods for process simulation. Boston: Butterworths, 1989.

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G, Samper Katia, and Haghi Reza K, eds. Advanced process control & simulation for chemical engineers. Toronto: Apple Academic Press, 2013.

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Distillation design and control using Aspen simulation. Hoboken, N.J: Wiley, 2006.

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Luca, Ferrarini, and Veber Carlo, eds. Modeling, control, simulation, and diagnosis of complex industrial and energy systems. Research Triangle Park, NC: Instrumentation Systems, and Automation Society, 2009.

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Joppich, Wolfgang. Multigrid Methods for Process Simulation. Vienna: Springer Vienna, 1993.

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Joppich, Wolfgang, and Slobodan Mijalković. Multigrid Methods for Process Simulation. Vienna: Springer Vienna, 1993. http://dx.doi.org/10.1007/978-3-7091-9253-5.

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Pelechano, Nuria, Jan M. Allbeck, and Norman I. Badler. Virtual Crowds: Methods, Simulation, and Control. Cham: Springer International Publishing, 2008. http://dx.doi.org/10.1007/978-3-031-79242-7.

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M, Allbeck Jan, and Badler Norman I, eds. Virtual crowds: Methods, simulation, and control. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2008.

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L, Mamzic C., ed. Statistical process control. Research Triangle Park, NC, U.S.A: Instrument Society of America, 1995.

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Book chapters on the topic "Process control Simulation methods"

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Katebi, Reza, Michael A. Johnson, and Jacqueline Wilkie. "Process Modelling and Simulation Methods." In Advances in Industrial Control, 1–37. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0423-0_1.

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Marquardt, W. "Numerical Methods for the Simulation of Differential-Algebraic Process Models." In Methods of Model Based Process Control, 41–79. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0135-6_2.

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Wang, Jing, Jinglin Zhou, and Xiaolu Chen. "Simulation Platform for Fault Diagnosis." In Intelligent Control and Learning Systems, 45–58. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8044-1_4.

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AbstractThe previous chapters have described the mathematical principles and algorithms of multivariate statistical methods, as well as the monitoring processes when used for fault diagnosis. In order to validate the effectiveness of data-driven multivariate statistical analysis methods in the field of fault diagnosis, it is necessary to conduct the corresponding fault monitoring experiments. Therefore this chapter introduces two kinds of simulation platform, Tennessee Eastman (TE) process simulation system and fed-batch Penicillin Fermentation Process simulation system. They are widely used as test platforms for the process monitoring, fault classification, and identification of industrial process. The related experiments based on PCA, CCA, PLS, and FDA are completed on the TE simulation platforms.
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de Saporta, Benoîte, François Dufour, and Huilong Zhang. "Optimal Impulse Control." In Numerical Methods for Simulation and Optimization of Piecewise Deterministic Markov Processes, 231–67. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119145066.ch10.

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Roffel, Brian, and Ben H. Betlem. "Process Simulation." In Advanced Practical Process Control, 33–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18258-7_2.

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Hintermüller, Michael, Michael Hinze, Christian Kahle, and Tobias Keil. "Fully Adaptive and Integrated Numerical Methods for the Simulation and Control of Variable Density Multiphase Flows Governed by Diffuse Interface Models." In Transport Processes at Fluidic Interfaces, 305–53. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56602-3_13.

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Goel, Shilpi, Anna Slobodova, Rob Sumners, and Sol Swords. "Balancing Automation and Control for Formal Verification of Microprocessors." In Computer Aided Verification, 26–45. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_2.

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AbstractFormal methods are becoming an indispensable part of the design process in software and hardware industry. It takes robust tools and proofs to make formal validation of large scale projects reliable. In this paper, we will describe the current status of formal verification at Centaur Technology. We will explain our challenges and our methodology—how various proofs and verification artifacts are interconnected and how we keep them consistent over the duration of a project. We also describe our main engine—a powerful symbolic simulator with rewriting capabilities that is integrated in a theorem prover and proven correct.
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Böhme, Berndt, Ralf Wieland, and Uwe Starke. "Knowledge Based Process Control." In Advances in Simulation, 419–22. New York, NY: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-6389-7_83.

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Vogel, Ernest F. "Plantwide Process Control Simulation." In Practical Distillation Control, 86–95. New York, NY: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4757-0277-4_6.

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Corriou, Jean-Pierre. "Models and Methods for Parametric Identification." In Process Control, 419–54. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61143-3_11.

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Conference papers on the topic "Process control Simulation methods"

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Futo, Jozef, Frantisek Krepelka, and Lucia Ivanicova. "Optimization of rock cutting process using the simulation methods." In 2011 12th International Carpathian Control Conference (ICCC). IEEE, 2011. http://dx.doi.org/10.1109/carpathiancc.2011.5945829.

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Byrski, Witold, and Michal Drapala. "Adaptive identification method for simulation and control of glass melting process." In 2019 24th International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2019. http://dx.doi.org/10.1109/mmar.2019.8864721.

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Hora, P., J. Heingärtner, N. Manopulo, and L. Tong. "Zero Failure Production Methods Based on a Process Integrated Virtual Control." In THE 8TH INTERNATIONAL CONFERENCE AND WORKSHOP ON NUMERICAL SIMULATION OF 3D SHEET METAL FORMING PROCESSES (NUMISHEET 2011). AIP, 2011. http://dx.doi.org/10.1063/1.3623590.

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Schne, Tamas, and Tibor Holczinger. "Coloured Petri Net based PLC program validation with a fast simulation method." In 2013 International Conference on Process Control (PC). IEEE, 2013. http://dx.doi.org/10.1109/pc.2013.6581405.

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Wang, Junsheng, Zhang Yan, Kunkui Wu, and Lei Song. "Simulation to coating weight control for galvanizing." In THE 11TH INTERNATIONAL CONFERENCE ON NUMERICAL METHODS IN INDUSTRIAL FORMING PROCESSES: NUMIFORM 2013. AIP, 2013. http://dx.doi.org/10.1063/1.4806908.

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Ozana, Stepan, and Tomas Docekal. "Numerical methods for discretization of continuous nonlinear systems used in SIL/PIL/HIL simulations." In 2019 22nd International Conference on Process Control (PC19). IEEE, 2019. http://dx.doi.org/10.1109/pc.2019.8815330.

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Wang, Guangji, and Gang Liu. "The Movement Process Simulation of CRDM." In 2017 25th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icone25-66857.

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The motion of CRDM (Control Rod Drive Mechanism) is affected by the electro-magnetic force and the fluid resistance, also the movement process affected the control system. In this paper, we considered all the coupled factor and try to decouple the problem to several simple problems. We supposed 3 decoupling methods, and try to verification each assumption, and finally we found that an assumption is valid — the electromagnetic force is mainly affected by the displacement of CRDM in the attract process of kinetic jaw armature and kinetic jaw magnetic pole. We studied the fluid resistance force by CFD simulation, and exported the force to the electromagnetic model which is built by Infolytica/Magnet, the control system model is built by Matlab/Simulink coupling interface. In order to simulate the continuous movement process of CRDM, we studied the boundary data at each time period, and linked each period by in-house code. Then we tested the coupling simulation, listed the duration time of electric current and the movement duration time of mechanism. Compare to the test data, the maximum error is 17%. On the whole, this solution coupled CFD, electro-magnetic and control system, the simulation result can help engineers to optimize the control algorithm and shape design in a certain extent.
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Ganeshmurthy, Saravanan, and Sayed A. Nassar. "Finite Element Simulation of Process Control of Bolt Tightening for Joints With Non-Parallel Contact." In ASME 2012 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/pvp2012-78508.

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In this paper, 3-D finite element analysis (FEA) is used for simulating and evaluating the various process control methods that are commonly used in the automated assembly of bolted joints. A joint model with non-parallel contact under the bolt head is used. The FEA model takes into account the thread helix angle of the fastener. Simulation includes the torque-only and the torque-turn process control methods for achieving a desired level of the bolt preload at initial assembly of the joint. The torque-only process control option is simulated by applying a target peak torque value at which the tightening process is stopped. On the other hand, a torque-angle method is simulated by first applying a low level (threshold) torque (to the bolt head) after which the bolt head (or nut) would be rotated by a specified angle of turn, in order to achieve the desired bolt tension. The effect of thread and underhead bearing friction coefficients as well as the hole size are investigated. The FEA simulation provided in this study would be helpful for developing reliable tightening strategies for joints with (as cast) non-parallel bearing surfaces.
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Chen, Weifeng, Lingyu Zhu, Xi Chen, and Zhijiang Shao. "Sensitivity embedded homotopy-based backtracking method for chemical process simulation." In 2013 10th IEEE International Conference on Control and Automation (ICCA). IEEE, 2013. http://dx.doi.org/10.1109/icca.2013.6565028.

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Jiao, Zhijie, Ruiyu Gao, Chunyu He, and Jun Wang. "Simulation Method of Rolling Mill Process Control System with Actual Information." In 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icmia-16.2016.94.

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Reports on the topic "Process control Simulation methods"

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Quinn, William. Driving Down HB-LED Costs. Implementation of Process Simulation Tools and Temperature Control Methods of High Yield MOCVD Growth. Office of Scientific and Technical Information (OSTI), April 2012. http://dx.doi.org/10.2172/1053618.

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Khvostina, Inesa, Serhiy Semerikov, Oleh Yatsiuk, Nadiia Daliak, Olha Romanko, and Ekaterina Shmeltser. Casual analysis of financial and operational risks of oil and gas companies in condition of emergent economy. [б. в.], October 2020. http://dx.doi.org/10.31812/123456789/4120.

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The need to control the risk that accompanies businesses in their day- to-day operations, and at the same time changing economic conditions make risk management an almost indispensable element of economic life. Selection of the main aspects of the selected phases of the risk management process: risk identification and risk assessment are related to their direct relationship with the subject matter (risk identification to be managed; risk analysis leading to the establishment of a risk hierarchy, and, consequently, the definition of risk control’ methods) and its purpose (bringing the risk to acceptable level). It is impossible to identify the basic patterns of development of the oil and gas industry without exploring the relationship between economic processes and enterprise risks. The latter are subject to simulation, and based on models it is possible to determine with certain probability whether there have been qualitative and quantitative changes in the processes, in their mutual influence on each other, etc. The work is devoted to exploring the possibilities of applying the Granger test to examine the causal relationship between the risks and obligations of oil and gas companies. The analysis is based on statistical tests and the use of linear regression models.
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Diahyleva, Olena S., Igor V. Gritsuk, Olena Y. Kononova, and Alona Y. Yurzhenko. Computerized adaptive testing in educational electronic environment of maritime higher education institutions. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4448.

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The article is devoted to the organization of modern learning process, namely the use of innovative technologies – computerized adaptive testing in educational electronic environment of maritime higher education institutions. The example of educational electronic environment is presented in the article on LMS Moodle. The provided new technological and methodological opportunities are a priority in the developed methods of control and testing of knowledge, skills and abilities of students. Comparative characteristic of using computerized adaptive testing in educational electronic environment is given in the article according to different criteria: the role of tests in the learning process; methods of training; equipment; presence of the problems in educational process; level of its control and learning outcomes. The paper also presents examples of activities to form communicative competency of future maritime professionals. Types of adaptive tests are listed in the paper. The research activities were done by second year cadets of ship engineering department of Maritime College of Kherson State Maritime Academy. The experiment was devoted to the formation of communicative competence with the help of electronic environment of maritime higher education institution. The results of experiment proved positive impact of computerized adaptive testing on communicative competence of future ship engineers. Further investigation of adaptive testing can also be done for learning system of maritime education establishments using simulation technologies of virtual, augmented and mixed realities.
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Voloshynov, Serhii A., Halyna V. Popova, Alona Y. Yurzhenko, and Ekaterina O. Shmeltser. The use of digital escape room in educational electronic environment of maritime higher education institutions. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3869.

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The paper is tended to investigate the gamification activities use in educational electronic environment of maritime higher education institutions. Gamification methods with examples are described (gamification testing, QR Code quest, storytelling and escape room). Comparative characteristic of traditional learning and learning using gamification in educational electronic environment is given in the article according to different criteria: the place and role of teacher or students in the learning process; type of information communication; methods of training; equipment; level of freedom of the actions; presence of the problems in educational process; level of its control and learning outcomes. The paper also presents examples of gamification activities based on escape room quest to form communicative competency of future maritime professionals. Escape room activity presented in the article contains storytelling element, crossword and electronic testing questions of different types. Question types listed in the paper are Drag and drop to the text, Short answer and Multiple choice. Escape room activity was done by second year cadets of Kherson State Maritime Academy. According to the received results, knowledge quality increased by 10% and success by 20%. Further investigation of gamification activities can also be done for learning system of maritime higher education institutions using simulation technologies of virtual, augmented and mixed realities.
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Spence, P. A., L. I. Weingarten, K. Schroder, D. M. Tung, and D. A. Sheaffer. Process control of large-scale finite element simulation software. Office of Scientific and Technical Information (OSTI), February 1996. http://dx.doi.org/10.2172/205962.

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Krajcsik, Stephen. The Use of Statistical Methods in Dimensional Process Control. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada444590.

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Sanders, William R. Measurement Methods for Human Performance in Command and Control Simulation Experiments. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada413273.

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Raboin, P. J. ,. LLNL. Integration of adaptive process control with computational simulation for spin-forming. Office of Scientific and Technical Information (OSTI), March 1998. http://dx.doi.org/10.2172/657365.

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Zalewski, Daniel J. Methods for Monitoring Process Control and Capability in the Presence of Autocorrelation. Fort Belvoir, VA: Defense Technical Information Center, August 1995. http://dx.doi.org/10.21236/ada305758.

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Goldman, D. S. Investigation of potential analytical methods for redox control of the vitrification process. [Moessbauer]. Office of Scientific and Technical Information (OSTI), November 1985. http://dx.doi.org/10.2172/6357185.

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