Relevant bibliographies by topics / Real-Time Process Optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Real-Time Process Optimization'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Real-Time Process Optimization"

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Bybee, Karen. "Real-Time Drilling-Process Optimization." Journal of Petroleum Technology 61, no. 08 (2009): 59–60. http://dx.doi.org/10.2118/0809-0059-jpt.

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Ajayi, Rhoda. "Integrating IoT and cloud computing for continuous process optimization in real time systems." International Journal of Research Publication and Reviews 6, no. 1 (2025): 2540–58. https://doi.org/10.55248/gengpi.6.0125.0441.

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Zhijiang, Shao, Wang Jinlin, and Qian Jixin. "Real-time Optimization of Acetaldehyde Production Process." Developments in Chemical Engineering and Mineral Processing 13, no. 3-4 (2008): 249–58. http://dx.doi.org/10.1002/apj.5500130306.

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Limanond, Suttipan, and Jennie Si. "RIE process time optimization from real time sensory data." IFAC Proceedings Volumes 32, no. 2 (1999): 443–48. http://dx.doi.org/10.1016/s1474-6670(17)56076-0.

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Miletic, I. P., and T. E. Marlin. "Results diagnosis for real-time process operations optimization." Computers & Chemical Engineering 22 (March 1998): S475—S482. http://dx.doi.org/10.1016/s0098-1354(98)00090-8.

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Boss, Edinara Adelaide, Rubens Maciel Filho, and Eduardo Coselli Vasco de Toledo. "Freeze drying process: real time model and optimization." Chemical Engineering and Processing: Process Intensification 43, no. 12 (2004): 1475–85. http://dx.doi.org/10.1016/j.cep.2004.01.005.

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Li, Dequn, Huamin Zhou, Peng Zhao, and Yang Li. "A real-time process optimization system for injection molding." Polymer Engineering & Science 49, no. 10 (2009): 2031–40. http://dx.doi.org/10.1002/pen.21444.

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Brooks, J. W. "Real-Time Data Capture Supports Process Modelling." Measurement and Control 35, no. 3 (2002): 69–71. http://dx.doi.org/10.1177/002029400203500302.

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This paper considers the real-time measurement and logging of physical variables from the forging process to enhance modelling of that process. The measurement problem is acute since environmental conditions are not ideal. The logging system is described and an approach is presented for the generation of accurate flow stress data. Improvements upon earlier efforts are discussed in the light of experience with modelling packages. The importance of accurate data for materials and machinery are highlighted.
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Huang, Jingwen, and Hongguang Li. "Plant-Wide Process Real-Time Optimization Based on Process Goose Queue Methodology." Procedia Engineering 29 (2012): 2526–31. http://dx.doi.org/10.1016/j.proeng.2012.01.345.

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Jeang, A., C.-C. Tsai, and C.-P. Chung. "Scheme for real-time process planning under process deterioration." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 223, no. 9 (2009): 1181–92. http://dx.doi.org/10.1243/09544054jem1356.

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Conventional approaches for process planning of manufacturing operations preset fixed process means and process tolerances for all operations and permit outputs to be distributed around these fixed values, provided that the final outputs meet acceptable specifications. These approaches are inappropriate for high-value and precision manufacturing processes, especially those where a complex part may suffer from process deterioration. The problem is that in these approaches, process means and process tolerances are considered to be independent decision variables, whereby the resultant process mea
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Dissertations / Theses on the topic "Real-Time Process Optimization"

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Chaudhary, Muhammad Nadeem Rafique. "Real time optimization of chemical processes." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/1419.

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Due to current changes in the global market with increasing competition, strict bounds on product specifications, pricing pressures, and environmental issues, the chemical process industry has a high demand for methods and tools that enhance profitability by reducing the operating costs using limited resources. Real time optimization (RTO) strategies combine process control and economics, and have gone through much advancement during the last few decades. A typical real time optimization application is model based and requires the solution of at least three (usually) nonlinear programming prob
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Benndorf, Jörg, and Mike Buxton. "Real-Time Mining - a framework for continuous process control and optimization." Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2018. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-231071.

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The flow of information, and consequently the decision-making along the chain of mining from exploration to beneficiation, typically occurs in a discontinuous fashion over long timespans. In addition, due to the uncertain nature of the knowledge about deposits and the inherent spatial distribution of material characteristics, actual production performance often deviates from expectations. Reconciliation exercises to adjust mineral resource and reserve models and planning assumptions are performed with timely lags of weeks, months or even years.
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Benndorf, Jörg, and Mike Buxton. "Real-Time Mining - a framework for continuous process control and optimization." TU Bergakademie Freiberg, 2017. https://tubaf.qucosa.de/id/qucosa%3A23172.

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The flow of information, and consequently the decision-making along the chain of mining from exploration to beneficiation, typically occurs in a discontinuous fashion over long timespans. In addition, due to the uncertain nature of the knowledge about deposits and the inherent spatial distribution of material characteristics, actual production performance often deviates from expectations. Reconciliation exercises to adjust mineral resource and reserve models and planning assumptions are performed with timely lags of weeks, months or even years.
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Tosukhowong, Thidarat. "Dynamic Real-time Optimization and Control of an Integrated Plant." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14087.

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Applications of the existing steady-state plant-wide optimization and the single-scale fast-rate dynamic optimization strategies to an integrated plant with material recycle have been impeded by several factors. While the steady-state optimization formulation is very simple, the very long transient dynamics of an integrated plant have limited the optimizers execution rate to be extremely low, yielding a suboptimal performance. In contrast, performing dynamic plant-wide optimization at the same rate as local controllers requires exorbitant on-line computational load and may increase the sensiti
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Graciano, José Eduardo Alves. "Real time optimization in chemical process: evaluation of strategies, improvements and industrial application." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/3/3137/tde-12072016-094348/.

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The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefit
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Rajendran, Ajith, and Gautham Asokan. "Real Time Monitoring of Machining Process and Data Gathering for Digital Twin Optimization." Thesis, KTH, Industriell produktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301594.

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In the development stages of a Digital twin of production assets, especially machine tools, real time process monitoring and data gathering proves to be vital. Having a monitoring system that monitors and updates the operators or managers in real time, helps improve productivity in terms of reducing downtime through predictive/preventive analytics and by incorporating in process quality assessment capabilities. When it comes to Real time monitoring of machine tools andprocesses, sensor technologies have proven to be the most effective and widely researched. Years of research and development ha
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Zanin, Antônio Carlos. "Implementação industrial de um otimizador em tempo real." Universidade de São Paulo, 2001. http://www.teses.usp.br/teses/disponiveis/3/3137/tde-06082001-150353/.

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Esta tese descreve o desenvolvimento e implementação de um otimizador em tempo real da operação do conversor da unidade de craqueamento catalítico em leito fluidizado (FCC) da refinaria Henrique Lage localizada em São José dos Campos. É desenvolvida uma estratégia de otimização integrada ao controlador preditivo cuja função objetivo e restrições incorporam componentes dinâmicos e estáticos. Os problemas de controle multivariável e otimização econômica são resolvidos simultaneamente num mesmo algoritmo. É utilizado um modelo rigoroso do processo para determinar as condições econômicas ótimas d
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Schultz, Eduardo dos Santos. "A importância do ponto de operação nas técnicas de self-optimizing control." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/127932.

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A otimização de processos vem se tornando uma ferramenta fundamental para o aumento da lucratividade das plantas químicas. Diversos métodos de otimização foram propostos ao longo dos anos, sendo que a otimização em tempo real (RTO) é a solução mais consolidada industrialmente, enquanto que o self-optimizing control (SOC) surge como uma alternativa simplificada, com um menor custo de implantação em relação a esse. Neste trabalho são estudados diversos aspectos da metodologia de SOC, iniciando pela análise do impacto do ponto de operação para o desenvolvimento de estruturas de controle auto-otim
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Yélamos, Ruiz Ignacio. "A global approach for supporting operators' decision-making dealing with plant abnormal events." Doctoral thesis, Universitat Politècnica de Catalunya, 2008. http://hdl.handle.net/10803/6465.

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El alto grado de automatización adquirido en las plantas químicas durante las últimas décadas hace que las tareas de supervisión sean ahora más complejas y delicadas. Esta supervisión requiere de sistemas y herramientas sofisticadas que puedan sacar provecho de los módulos de adquisición de información instalados en planta. Así, el preciso seguimiento de las variables de proceso o la fácil operatividad de los procesos, gracias a los sistemas de control regulatorio actuales, son aspectos relevantes que deben ser contemplados a la hora de dar una respuesta global a las desviaciones del régimen n
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García, Lina Marcela Palacio. "Metodologias de análise de dados para um sistema de otimização em tempo real." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/3/3137/tde-01082013-161137/.

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A otimização em tempo real (RTO: Real Time Optimization) permite fazer correções, com o menor atraso possível, nas condições de operação de um processo, buscando manter um desempenho ótimo. A RTO, na abordagem clássica, requer um ciclo constante de análise e correção do estado do processo que inclui múltiplas etapas: i) identificação do estado estacionário, ii) identificação e correção dos erros grosseiros, iii) reconciliação dos dados, iv) ajuste dos parâmetros do modelo, v) estimação das condições operacionais ótimas e, vi) implementação das condições no sistema de controle. Um sistema de an
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Books on the topic "Real-Time Process Optimization"

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Jain, Madhu, Chandra Shekhar, Rakhee Kulshrestha, and Srinivas R. Chakravarthy. Mathematical Modeling and Computation of Real-Time Problems. Taylor & Francis Group, 2021.

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Mathematical Modeling and Computation of Real-Time Problems: An Interdisciplinary Approach. CRC Press LLC, 2020.

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Jain, Madhu, Chandra Shekhar, Rakhee Kulshrestha, and Srinivas R. Chakravarthy. Mathematical Modeling and Computation of Real-Time Problems: An Interdisciplinary Approach. Taylor & Francis Group, 2021.

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Mathematical Modeling and Computation of Real-Time Problems: An Interdisciplinary Approach. Taylor & Francis Group, 2021.

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Hilgurt, S. Ya, and O. A. Chemerys. Reconfigurable signature-based information security tools of computer systems. PH “Akademperiodyka”, 2022. http://dx.doi.org/10.15407/akademperiodyka.458.297.

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The book is devoted to the research and development of methods for combining computational structures for reconfigurable signature-based information protection tools for computer systems and networks in order to increase their efficiency. Network security tools based, among others, on such AI-based approaches as deep neural networking, despite the great progress shown in recent years, still suffer from nonzero recognition error probability. Even a low probability of such an error in a critical infrastructure can be disastrous. Therefore, signature-based recognition methods with their theoretic
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Book chapters on the topic "Real-Time Process Optimization"

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Wang, Jian. "Real Time Optimization of Ketone-Benzol Dewaxing Process." In A Self Adaptive Real Time Optimization for Stochastic Dynamic System. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-0632-0_16.

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Kiparissides, C., E. Papadopoulos, and J. Morris. "Real-Time Optimization and Model-Based Control of Polymer Reactors." In Methods of Model Based Process Control. Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0135-6_19.

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Luo, Hao. "Real-Time Configuration Techniques for PnP Process Monitoring." In Plug-and-Play Monitoring and Performance Optimization for Industrial Automation Processes. Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-15928-3_5.

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Garrido, Izaskun, and Marc C. Steinbach. "A Multistage Stochastic Programming Approach in Real-Time Process Control." In Online Optimization of Large Scale Systems. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04331-8_25.

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Papacharalampopoulos, Alexios, and Panagiotis Stavropoulos. "Manufacturing Process Optimization via Digital Twins: Definitions and Limitations." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18326-3_33.

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AbstractManufacturing process real-time optimization has been one of the main digital twins’ operations. It is of utmost importance to the processes, since it enables the feedback of a digital twin towards the real world. However, it is quite difficult to be implemented, since it requires modelling of the process, adaptivity of both the model and the process, real-time communication and link to other functionalities. Under the framework of formalizing such activities, the current work attempts to categorize the types of manufacturing process real-time optimization and show their limitations. F
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Potyrailo, Radislav A., Ronald J. Wroczynski, John P. Lemmon, William P. Flanagan, and Oltea P. Siclovan. "Multivariate Tools for Real-Time Monitoring and Optimization of Combinatorial Materials and Process Conditions." In Analysis and Purification Methods in Combinatorial Chemistry. John Wiley & Sons, Inc., 2004. http://dx.doi.org/10.1002/0471531979.ch5.

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Rostamian, A., M. Rappaz, M. Bertherat, J. L. Desbiolles, and M. A. Salgado Ordorica. "Aluminium Melting Process Optimization with SmartMelt, a Digital Tool for Real-Time Operational Guidance." In Light Metals 2022. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92529-1_94.

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Costa, Daniella, Rodrigo Neves, Fernando Melo, et al. "Steam Grid Stability Using Advanced Process Control and Real Time Optimization in an Alumina Refinery." In The Minerals, Metals & Materials Series. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-22532-1_25.

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Fang, Bin, Shi Zhu, Hongyu Zhu, Ziqian Zhang, Ye Tao, and Yubin Sheng. "Optimization of Real-Time Power Grid Measurement Data Scheduling Based on Genetic Algorithms." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2409-6_22.

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Abstract An increasing demand of real-time monitoring and data analysis for the power grid, is facing challenges from the processing rate of massive real-time measurement data such as voltage, current and power from billions of sensors. To guarantee process rate, many measurement data scheduling method had been studied, while the problem for the balance of realtime requirement and load balance has not been solved well, which leads to uneven load distribution and data congestion. Thus, this paper proposed a measurement data scheduling method based on genetic algorithm. The proposed method consi
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Idzik, Christian, Daniel Hilger, Norbert Hosters, et al. "Decision Support for the Optimization of Continuous Processesusing Digital Shadows." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-44497-5_12.

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AbstractDecision support systems can provide real-time process information and correlations, which in turn assists process experts in making decisions and thus further increase productivity. This also applies to well-established and already highly automated processes in continuous production employed in various industrial sectors. Continuous production refers to processes in which the produced material, either fluid or solid form, is continuously in motion and processed. As a result, the process can usually not be stopped. It is only possible to influence the running process. However, the high
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Conference papers on the topic "Real-Time Process Optimization"

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Jena, Kasinath, Sandeep Kumar Jain, and Srinivasa Rao K. S. "Real-Time Vision Tracking for Assembly Line Process Optimization." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10724693.

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Damiri, Hazem, Martin Steinberger, and Martin Horn. "Real Time Optimization of a Continuous Pharmaceutical Manufacturing Process Based on Hammerstein Models." In 2025 25th International Conference on Process Control (PC). IEEE, 2025. https://doi.org/10.1109/pc65047.2025.11047386.

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Matias, Jos�, and Alvaro Acevedo. "Production scheduling based on Real-time Optimization and Zone Control Nonlinear Model Predictive Controller." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.126350.

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The motivation of this work is an application of a production scheduling based on Real-Time Optimization and Zone Control Nonlinear Model Predictive Controller on a liquid recovery unit of an LPG production plant. In this unit, the scheduling-relevant disturbances occur on a time scale relevant to the system dynamics; thus, we propose a novel combination of a well-known control strategies leading to a hierarchical two-layered strategy, where the lower layer employs a zone control nonlinear model predictive controller (NMPC) to define inventory setpoints while the upper layer uses real-time opt
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Pasieka, Engelbert, and Sebastian Engell. "Evolutionary Algorithm Based Real-time Scheduling via Simulation-Optimization for Multiproduct Batch Plants." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.183349.

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Production scheduling in the process industry is an area of significant activity in research and of great practical importance for the performance of industrial companies. In the vast majority of research papers, the scheduling problem is formulated as an off-line problem where a number of jobs is scheduled on a number of resources and the efficiency of the formulation and the solution algorithms is discussed. In reality, however, scheduling is a continuous activity that has to react to the arrival of new orders, to variations in processing times, breakdowns, lack of resources etc. This is ter
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Szabo, L. F., M. I. McElroy, L. J. Miller, and G. F. Hays. "Controlling Corrosion in a Real-Time Environment: Fundamentals of Automatic Control in “Real-Time”." In CORROSION 2009. NACE International, 2009. https://doi.org/10.5006/c2009-09460.

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Abstract It is estimated that corrosion costs industries hundreds of billions of dollars annually. Many of the costs directly related to corrosion may be mitigated and managed with continuously monitored corrosion transmitters as part of a comprehensive plant-wide control strategy. Process parameter effects related to electrochemical corrosion may be minimized via direct, continuous corrosion feedback for active control and optimization of neutralizing agents, e.g. inhibitors. This paper details the investigation into corrosion control strategies and provides recommendations on optimal process
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Ding, Lichen, Yuta Onishi, Osamu Yamanaka, and Yuki Nishimuro. "Real-Time Optimization of The Wastewater Treatment Process Utilizing a Linear Approximation-Based Extremum Seeking." In 2024 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2024. http://dx.doi.org/10.1109/ccta60707.2024.10666534.

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Iqbal, Imam M., Xinyu Wang, Isabell Viedt, and Leonhard Urbas. "Leveraging Machine Learning for Real-Time Performance Prediction of Near Infrared Separators in Waste Sorting Plant." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.130911.

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Many small and medium enterprises (SME) often fail to fully utilize the data they collect due to a lack of technical expertise. The ecoKI platform, a low-code solution that simplifies machine learning application for SMEs, showed a promising answer to the challenge. This study explores the application of ecoKI platform to design process monitoring tools for waste sorting plants. NIR separator data were processed through ecoKI�s building blocks to train two neural network architectures�MLP and LSTM�for predicting NIR separation efficiency. The results showed that the models accurately predicted
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Rommetveit, Tarjei, Roy Johnsen, and Øystein Baltzersen. "Using Ultrasound Measurements for Real-Time Process Control of Pipelines and Process Equipment Subjected to Corrosion And/or Erosion." In CORROSION 2008. NACE International, 2008. https://doi.org/10.5006/c2008-08285.

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Abstract Corrosion and erosion remain two key issues in petroleum production. In the last few years, there has been an increasing demand for online process control where the rate of metal loss may be monitored. From an ultrasound perspective these challenges reduce to measuring the wall thickness over time. By combining permanently installed sensors, low noise measurements and temperature compensation, lab experiments have shown that it is possible to detect changes in wall thickness on the sub micrometer scale. The results suggest that ultrasound technology is well suited for real time corros
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Wang, Yan. "Optimization Method for Startup Speed of Real-time Process Applications Based on Qt in Embedded Operating System." In 2024 4th International Symposium on Computer Technology and Information Science (ISCTIS). IEEE, 2024. http://dx.doi.org/10.1109/isctis63324.2024.10699253.

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Zhu, Mengjia, Oliver Pennington, Sam Kay, Amin Zarei, Michael Short, and Dongda Zhang. "Optimization-based operational space design for effective bioprocess performance under uncertainty." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.131628.

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Maintaining consistent product quality and yield in bioprocess operations is challenging due to uncertainties inherent in biological systems. Thus, robust strategies are essential to ensure key performance indicators (KPIs), such as product concentration and yield, are consistently met despite the uncertainties. Real-time feedback co Interntrol, though widely used, is often impractical due to its reliance on expensive sensors, rapid data processing, and high-speed control actions. This paper proposes a novel approach to address these challenges by identifying the operational space for control
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Reports on the topic "Real-Time Process Optimization"

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Videa, Aldo, and Yiyi Wang. Inference of Transit Passenger Counts and Waiting Time Using Wi-Fi Signals. Western Transportation Institute, 2021. http://dx.doi.org/10.15788/1715288737.

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Passenger data such as real-time origin-destination (OD) flows and waiting times are central to planning public transportation services and improving visitor experience. This project explored the use of Internet of Things (IoT) Technology to infer transit ridership and waiting time at bus stops. Specifically, this study explored the use of Raspberry Pi computers, which are small and inexpensive sets of hardware, to scan the Wi-Fi networks of passengers’ smartphones. The process was used to infer passenger counts and obtain information on passenger trajectories based on Global Positioning Syste
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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Rémy, Elisabeth, Romain Escudier, and Alexandre Mignot. Access impact of observations. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d4.8.

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The accuracy of the Copernicus Marine Environment and Monitoring Service (CMEMS) ocean analysis and forecasts highly depend on the availability and quality of observations to be assimilated. In situ observations are complementary to satellite observations that are restricted to the ocean surface. Higher resolution model forecasts are required by users of the CMEMS global and regional ocean analysis and forecasts. To support this with an efficient observational constrain of the model forecast via data assimilation, an increase observation coverage is needed, associated with an improved usage of
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