Integrated Process Modeling Advanced Control And Data Analytics For Optimizing Polyolefin Manufacturing 2 Volume Set

Author : Y. A. Liu,Niket Sharma
Publisher : Wiley-VCH
Page : 0 pages
File Size : 45,9 Mb
Release : 2023-07-24
Category : Technology & Engineering
ISBN : 3527352678

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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing, 2 Volume Set by Y. A. Liu,Niket Sharma Pdf

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.

Author : Yih An Liu,Niket Sharma
Publisher : Unknown
Page : 0 pages
File Size : 45,5 Mb
Release : 2023
Category : Polyolefin industry
ISBN : 3527352694

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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing by Yih An Liu,Niket Sharma Pdf

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.

Author : Y. A. Liu,Niket Sharma
Publisher : John Wiley & Sons
Page : 1027 pages
File Size : 47,7 Mb
Release : 2023-07-25
Category : Technology & Engineering
ISBN : 9783527843824

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Integrated Process Modeling, Advanced Control and Data Analytics for Optimizing Polyolefin Manufacturing by Y. A. Liu,Niket Sharma Pdf

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.

Author : Jose A. Romagnoli,Ahmet Palazoglu
Publisher : CRC Press
Page : 712 pages
File Size : 43,9 Mb
Release : 2020-07
Category : Science
ISBN : 0429351399

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Introduction to Process Control by Jose A. Romagnoli,Ahmet Palazoglu Pdf

Introduction to Process Control, Third Edition continues to provide a bridge between traditional and modern views of process control by blending conventional topics with a broader perspective of integrated process operation, control, and information systems. Updated and expanded throughout, this third edition addresses issues highly relevant to today's teaching of process control: Discusses smart manufacturing, new data preprocessing techniques, and machine learning and artificial intelligence concepts that are part of current smart manufacturing decisions Includes extensive references to guide the reader to the resources needed to solve modeling, classification, and monitoring problems 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 back-off 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 Analyzes 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 Drawing on the authors' combined 60 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 text offers a comprehensive pedagogical approach to reinforce learning and presents a concept first followed by an example, allowing students to grasp theoretical concepts in a practical manner and uses the same problem in each chapter, culminating in a complete control design strategy. A vast number of exercises throughout ensure readers are supported in their learning and comprehension. Downloadable MATLAB® toolboxes for process control education as well as the main simulation examples from the book offer a user-friendly software environment for interactively studying the examples in the text. These can be downloaded from the publisher's website. Solutions manual is available for qualifying professors from the publisher.

Author : Frank (Xin X.) Zhu
Publisher : John Wiley & Sons
Page : 48 pages
File Size : 51,5 Mb
Release : 2021-04-06
Category : Technology & Engineering
ISBN : 9781119634102

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Digitalization and Analytics for Smart Plant Performance by Frank (Xin X.) Zhu Pdf

This book addresses the topic of integrated digitization of plants on an objective basis and in a holistic manner by sharing data, applying analytics tools and integrating workflows via pertinent examples from industry. It begins with an evaluation of current performance management practices and an overview of the need for a "Connected Plant" via digitalization followed by sections on "Connected Assets: Improve Reliability and Utilization," "Connected Processes: Optimize Performance and Economic Margin " and "Connected People: Digitalizing the Workforce and Workflows and Developing Ownership and Digital Culture," then culminating in a final section entitled "Putting All Together Into an Intelligent Digital Twin Platform for Smart Operations and Demonstrated by Application cases."

Author : BARIS. DIANGELAKIS BURNAK (NIKOLAOS A. PISTIKOPOULOS, EFSTRATIOS N.),Nikolaos A. Diangelakis,Efstratios N. Pistikopoulos
Publisher : Synthesis Lectures on Engineer
Page : 258 pages
File Size : 44,5 Mb
Release : 2020-09-04
Category : Computers
ISBN : 1681739569

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Integrated Process Design and Operational Optimization Via Multiparametric Programming by BARIS. DIANGELAKIS BURNAK (NIKOLAOS A. PISTIKOPOULOS, EFSTRATIOS N.),Nikolaos A. Diangelakis,Efstratios N. Pistikopoulos Pdf

Author : Torsten P. Bohlin
Publisher : Springer Science & Business Media
Page : 351 pages
File Size : 51,8 Mb
Release : 2006-09-07
Category : Technology & Engineering
ISBN : 9781846284038

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Practical Grey-box Process Identification by Torsten P. Bohlin Pdf

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.

Author : Huamin Zhou
Publisher : John Wiley & Sons
Page : 40 pages
File Size : 49,6 Mb
Release : 2013-03-04
Category : Technology & Engineering
ISBN : 9780470602997

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Computer Modeling for Injection Molding by Huamin Zhou Pdf

This book covers a wide range of applications and uses of simulation and modeling techniques in polymer injection molding, filling a noticeable gap in the literature of design, manufacturing, and the use of plastics injection molding. The authors help readers solve problems in the advanced control, simulation, monitoring, and optimization of injection molding processes. The book provides a tool for researchers and engineers to calculate the mold filling, optimization of processing control, and quality estimation before prototype molding.

Author : Sandip K. Lahiri
Publisher : John Wiley & Sons
Page : 309 pages
File Size : 42,6 Mb
Release : 2017-10-23
Category : Technology & Engineering
ISBN : 9781119243601

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Multivariable Predictive Control by Sandip K. Lahiri Pdf

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.

Author : Sandip K. Lahiri
Publisher : John Wiley & Sons
Page : 432 pages
File Size : 49,8 Mb
Release : 2020-05-01
Category : Technology & Engineering
ISBN : 9781119532170

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Profit Maximization Techniques for Operating Chemical Plants by Sandip K. Lahiri Pdf

A systematic approach to profit optimization utilizing strategic solutions and methodologies for the chemical process industry In the ongoing battle to reduce the cost of production and increase profit margin within the chemical process industry, leaders are searching for new ways to deploy profit optimization strategies. Profit Maximization Techniques For Operating Chemical Plants defines strategic planning and implementation techniques for managers, senior executives, and technical service consultants to help increase profit margins. The book provides in-depth insight and practical tools to help readers find new and unique opportunities to implement profit optimization strategies. From identifying where the large profit improvement projects are to increasing plant capacity and pushing plant operations towards multiple constraints while maintaining continuous improvements—there is a plethora of information to help keep plant operations on budget. The book also includes information on: ● Take away methods and techniques for identifying and exploiting potential areas to improve profit within the plant ● Focus on latest Artificial Intelligence based modeling, knowledge discovery and optimization strategies to maximize profit in running plant. ● Describes procedure to develop advance process monitoring and fault diagnosis in running plant ● Thoughts on engineering design , best practices and monitoring to sustain profit improvements ● Step-by-step guides to identifying, building, and deploying improvement applications For leaders and technologists in the industry who want to maximize profit margins, this text provides basic concepts, guidelines, and step-by-step guides specifically for the chemical plant sector.

Author : Sina Ebnesajjad
Publisher : John Wiley & Sons
Page : 450 pages
File Size : 43,5 Mb
Release : 2021-04-13
Category : Technology & Engineering
ISBN : 9781119322979

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Concise Handbook of Fluorocarbon Gases by Sina Ebnesajjad Pdf

This book describes fluorocarbons gases’ preparation process, properties, applications and their evolution over time. The impact of fluorocarbons on the ozone layer and global and the development to mitigate those effects have been specially emphasized. The first major industrial fluorinated compound was developed in the 1920’s, to replace ammonia and sulfur dioxide refrigerants, at the General Motors Frigidaire Division by Thomas Midgley, Jr. and Albert Leon Henne. They developed a family of fluorocarbons trademarked Freon® for auto air conditioning units revolutionizing the auto industry. Other applications were developed over time including fire extinguishers, propellants, blowing agents, cleaners, anesthesia, artificial blood and others impacting every facet of life. In spite of being in broad global use for nearly a century, fluorocarbon gases have gone through great evolution during the last few decades. In the 1980s it was discovered chlorofluorocarbon (CFC) gases are harmful to the ozone layer, mainly because of their chlorine content. Chlorine was released in the upper atmosphere when chlorofluorocarbon molecules were broken down by the high energy cosmic radiation. CFCs were progressively banned following the Montreal Protocol of 1987. CFCs were replaced by fluorinated gases containing either less chlorine (hydrofluoro-chlorocarbons, or HCFCs), which are much less damaging (about 90% less) to the ozone layer or with fluorinated gases containing no chlorine, i.e. hydrofluorocarbons or HFCs. HFC have no impact on the ozone layer but impact global warming detrimentally. HFCs are usable without need for changes to the existing refrigeration or air conditioning installations. More recently hydrofluoroolefins (HFOs), which have little or no negative impact on global warming, have been developed to replace or reduce the use of HFCs. HFOs are used as single compounds or in blends. Research and development continues to develop and replace the HCFCs and HFCs completely with environmentally friendly products. Concise Handbook of Fluorocarbon Gases presents a reference and text for the commercial fluorocarbon gases which have great many application in a wide range of industries such as refrigeration and air conditioning, as well as consumer products.

Author : Sebastian Raschka,Yuxi (Hayden) Liu,Vahid Mirjalili
Publisher : Packt Publishing Ltd
Page : 775 pages
File Size : 55,9 Mb
Release : 2022-02-25
Category : Computers
ISBN : 9781801816380

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Machine Learning with PyTorch and Scikit-Learn by Sebastian Raschka,Yuxi (Hayden) Liu,Vahid Mirjalili Pdf

This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn applied machine learning with a solid foundation in theory Clear, intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices Book DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP). This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learn Explore frameworks, models, and techniques for machines to learn from data Use scikit-learn for machine learning and PyTorch for deep learning Train machine learning classifiers on images, text, and more Build and train neural networks, transformers, and boosting algorithms Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who this book is for If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.

Author : Kang Li
Publisher : John Wiley & Sons
Page : 316 pages
File Size : 46,6 Mb
Release : 2007-04-30
Category : Technology & Engineering
ISBN : 0470319461

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Ceramic Membranes for Separation and Reaction by Kang Li Pdf

Ceramic Membranes for Reaction and Separation is the first single-authored guide to the developing area of ceramic membranes. Starting by documenting established procedures of ceramic membrane preparation and characterization, this title then focuses on gas separation. The final chapter covers ceramic membrane reactors;- as distributors and separators, and general engineering considerations. Chapters include key examples to illustrate membrane synthesis, characterisation and applications in industry. Theoretical principles, advantages and disadvantages of using ceramic membranes under the various conditions are discussed where applicable.

Author : Antonio Coppola,Giovanni Carlo Di Renzo,Giuseppe Altieri,Paola D'Antonio
Publisher : Springer Nature
Page : 860 pages
File Size : 46,5 Mb
Release : 2020-03-19
Category : Science
ISBN : 9783030392994

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Innovative Biosystems Engineering for Sustainable Agriculture, Forestry and Food Production by Antonio Coppola,Giovanni Carlo Di Renzo,Giuseppe Altieri,Paola D'Antonio Pdf

This book gathers the latest advances, innovations, and applications in the field of innovative biosystems engineering for sustainable agriculture, forestry and food production. Focusing on the challenges of implementing sustainability in various contexts in the fields of biosystems engineering, it shows how the research has addressed the sustainable use of renewable and non-renewable resources. It also presents possible solutions to help achieve sustainable production. The Mid-Term Conference of the Italian Association of Agricultural Engineering (AIIA) is part of a series of conferences, seminars and meetings that the AIIA organizes, together with other public and private stakeholders, to promote the creation and dissemination of new knowledge in the sector. The contributions included in the book were selected by means of a rigorous peer-review process, and offer an extensive and multidisciplinary overview of interesting solutions in the field of innovative biosystems engineering for sustainable agriculture.

Author : Shlomo Kashani
Publisher : Unknown
Page : 128 pages
File Size : 43,9 Mb
Release : 2020-12-09
Category : Electronic
ISBN : 1034057251

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Deep Learning Interviews by Shlomo Kashani Pdf

The book's contents is a large inventory of numerous topics relevant to DL job interviews and graduate level exams. That places this work at the forefront of the growing trend in science to teach a core set of practical mathematical and computational skills. It is widely accepted that the training of every computer scientist must include the fundamental theorems of ML, and AI appears in the curriculum of nearly every university. This volume is designed as an excellent reference for graduates of such programs.