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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing, 2 Volume Set

Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing, 2 Volume Set
Author: Y. A. Liu
Publisher: Wiley-VCH
Total Pages: 0
Release: 2023-07-24
Genre: Technology & Engineering
ISBN: 9783527352678
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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing Detailed resource on the “Why,” “What,” and “How” of integrated process modeling, advanced control and data analytics explained via hands-on examples and workshops for optimizing polyolefin manufacturing. Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing discusses, as well as demonstrates, the optimization of polyolefin production by covering topics from polymer process modeling and advanced process control to data analytics and machine learning, and sustainable design and industrial practice. The text also covers practical problems, handling of real data streams, developing the right level of detail, and tuning models to the available data, among other topics, to allow for easy translation of concepts into practice. Written by two highly qualified authors, Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing includes information on: Segment-based modeling of polymer processes; selection of thermodynamic methods; estimation of physical properties for polymer process modeling Reactor modeling, convergence tips and data-fit tool; free radical polymerization (LDPE, EVA and PS), Ziegler-Natta polymerization (HDPE, PP, LLPDE, and EPDM) and ionic polymerization (SBS rubber) Improved polymer process operability and control through steady-state and dynamic simulation models Model-predictive control of polyolefin processes and applications of multivariate statistics and machine learning to optimizing polyolefin manufacturing Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing enables readers to make full use of advanced computer models and latest data analytics and machine learning tools for optimizing polyolefin manufacturing, making it an essential resource for undergraduate and graduate students, researchers, and new and experienced engineers involved in the polyolefin industry.

Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing

Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing
Author: Y. A. Liu
Publisher: John Wiley & Sons
Total Pages: 1027
Release: 2023-07-25
Genre: Technology & Engineering
ISBN: 3527843825
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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing Detailed resource on the “Why,” “What,” and “How” of integrated process modeling, advanced control and data analytics explained via hands-on examples and workshops for optimizing polyolefin manufacturing. Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing discusses, as well as demonstrates, the optimization of polyolefin production by covering topics from polymer process modeling and advanced process control to data analytics and machine learning, and sustainable design and industrial practice. The text also covers practical problems, handling of real data streams, developing the right level of detail, and tuning models to the available data, among other topics, to allow for easy translation of concepts into practice. Written by two highly qualified authors, Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing includes information on: Segment-based modeling of polymer processes; selection of thermodynamic methods; estimation of physical properties for polymer process modeling Reactor modeling, convergence tips and data-fit tool; free radical polymerization (LDPE, EVA and PS), Ziegler-Natta polymerization (HDPE, PP, LLPDE, and EPDM) and ionic polymerization (SBS rubber) Improved polymer process operability and control through steady-state and dynamic simulation models Model-predictive control of polyolefin processes and applications of multivariate statistics and machine learning to optimizing polyolefin manufacturing Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing enables readers to make full use of advanced computer models and latest data analytics and machine learning tools for optimizing polyolefin manufacturing, making it an essential resource for undergraduate and graduate students, researchers, and new and experienced engineers involved in the polyolefin industry.

Integrated Process Design and Operational Optimization via Multiparametric Programming

Integrated Process Design and Operational Optimization via Multiparametric Programming
Author: Baris Burnak
Publisher: Morgan & Claypool Publishers
Total Pages: 260
Release: 2020-09-04
Genre: Technology & Engineering
ISBN: 1681739550
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This book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers. In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.

Introduction to Process Control, Second Edition

Introduction to Process Control, Second Edition
Author: Jose A. Romagnoli
Publisher: CRC Press
Total Pages: 647
Release: 2012-02-14
Genre: Science
ISBN: 1439854866
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Introduction to Process Control, Second Edition provides a bridge between the traditional view of process control and the current, expanded role by blending conventional topics with a broader perspective of more integrated process operation, control, and information systems. Updating and expanding the content of its predecessor, this second edition addresses issues in today’s teaching of process control. Teaching & Learning Principles Presents a concept first followed by an example, allowing students to grasp theoretical concepts in a practical manner Uses the same problem in each chapter, culminating in a complete control design strategy Includes 50 percent more exercises Content Defines the traditional and expanded roles of process control in modern manufacturing Introduces the link between process optimization and process control (optimizing control), including the effect of disturbances on the optimal plant operation, the concepts of steady-state and dynamic backoff as ways to quantify the economic benefits of control, and how to determine an optimal transition policy during a planned production change Incorporates an introduction to the modern architectures of industrial computer control systems with real case studies and applications to pilot-scale operations Discusses the expanded role of process control in modern manufacturing, including model-centric technologies and integrated control systems Integrates data processing/reconciliation and intelligent monitoring in the overall control system architecture Web Resource The book’s website offers a user-friendly software environment for interactively studying the examples in the text. The site contains the MATLAB® toolboxes for process control education as well as the main simulation examples from the book. Access the site through the authors’ websites at www.pseonline.net and www.chms.ucdavis.edu/research/web/pse/ahmet/ Drawing on the authors’ combined 50 years of teaching experiences, this classroom-tested text is designed for chemical engineering students but is also suitable for industrial practitioners who need to understand key concepts of process control and how to implement them. The authors help readers see how traditional process control has evolved into an integrated operational environment used to run modern manufacturing facilities.

Practical Grey-box Process Identification

Practical Grey-box Process Identification
Author: Torsten P. Bohlin
Publisher: Springer Science & Business Media
Total Pages: 363
Release: 2006-09-07
Genre: Technology & Engineering
ISBN: 1846284031
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This book reviews the theoretical fundamentals of grey-box identification and puts the spotlight on MoCaVa, a MATLAB-compatible software tool, for facilitating the procedure of effective grey-box identification. It demonstrates the application of MoCaVa using two case studies drawn from the paper and steel industries. In addition, the book answers common questions which will help in building accurate models for systems with unknown inputs.

Multivariable Predictive Control

Multivariable Predictive Control
Author: Sandip K. Lahiri
Publisher: John Wiley & Sons
Total Pages: 309
Release: 2017-10-23
Genre: Technology & Engineering
ISBN: 1119243602
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A guide to all practical aspects of building, implementing, managing, and maintaining MPC applications in industrial plants Multivariable Predictive Control: Applications in Industry provides engineers with a thorough understanding of all practical aspects of multivariate predictive control (MPC) applications, as well as expert guidance on how to derive maximum benefit from those systems. Short on theory and long on step-by-step information, it covers everything plant process engineers and control engineers need to know about building, deploying, and managing MPC applications in their companies. MPC has more than proven itself to be one the most important tools for optimising plant operations on an ongoing basis. Companies, worldwide, across a range of industries are successfully using MPC systems to optimise materials and utility consumption, reduce waste, minimise pollution, and maximise production. Unfortunately, due in part to the lack of practical references, plant engineers are often at a loss as to how to manage and maintain MPC systems once the applications have been installed and the consultants and vendors’ reps have left the plant. Written by a chemical engineer with two decades of experience in operations and technical services at petrochemical companies, this book fills that regrettable gap in the professional literature. Provides a cost-benefit analysis of typical MPC projects and reviews commercially available MPC software packages Details software implementation steps, as well as techniques for successfully evaluating and monitoring software performance once it has been installed Features case studies and real-world examples from industries, worldwide, illustrating the advantages and common pitfalls of MPC systems Describes MPC application failures in an array of companies, exposes the root causes of those failures, and offers proven safeguards and corrective measures for avoiding similar failures Multivariable Predictive Control: Applications in Industry is an indispensable resource for plant process engineers and control engineers working in chemical plants, petrochemical companies, and oil refineries in which MPC systems already are operational, or where MPC implementations are being considering.

Additive Manufacturing

Additive Manufacturing
Author: Amit Bandyopadhyay
Publisher: CRC Press
Total Pages: 547
Release: 2015-09-08
Genre: Technology & Engineering
ISBN: 1498766706
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The field of additive manufacturing has seen explosive growth in recent years due largely in part to renewed interest from the manufacturing sector. Conceptually, additive manufacturing, or industrial 3D printing, is a way to build parts without using any part-specific tooling or dies from the computer-aided design (CAD) file of the part. Today, mo

Refinery Engineering

Refinery Engineering
Author: Ai-Fu Chang
Publisher: John Wiley & Sons
Total Pages: 521
Release: 2013-03-01
Genre: Technology & Engineering
ISBN: 3527666850
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A pioneering and comprehensive introduction to the complex subject of integrated refinery process simulation, using many of the tools and techniques currently employed in modern refineries. Adopting a systematic and practical approach, the authors include the theory, case studies and hands-on workshops, explaining how to work with real data. As a result, senior-level undergraduate and graduate students, as well as industrial engineers learn how to develop and use the latest computer models for the predictive modeling and optimization of integrated refinery processes. Additional material is available online providing relevant spreadsheets and simulation files for all the models and examples presented in the book.

Fault Detection and Diagnosis in Industrial Systems

Fault Detection and Diagnosis in Industrial Systems
Author: L.H. Chiang
Publisher: Springer Science & Business Media
Total Pages: 281
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1447103475
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Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.

Advances in Communication and Computational Technology

Advances in Communication and Computational Technology
Author: Gurdeep Singh Hura
Publisher: Springer Nature
Total Pages: 1498
Release: 2020-08-13
Genre: Technology & Engineering
ISBN: 9811553416
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This book presents high-quality peer-reviewed papers from the International Conference on Advanced Communication and Computational Technology (ICACCT) 2019 held at the National Institute of Technology, Kurukshetra, India. The contents are broadly divided into four parts: (i) Advanced Computing, (ii) Communication and Networking, (iii) VLSI and Embedded Systems, and (iv) Optimization Techniques.The major focus is on emerging computing technologies and their applications in the domain of communication and networking. The book will prove useful for engineers and researchers working on physical, data link and transport layers of communication protocols. Also, this will be useful for industry professionals interested in manufacturing of communication devices, modems, routers etc. with enhanced computational and data handling capacities.