Download or read book Machining Process Monitoring Using Multivariate Latent Variable Methods written by Mahmoud Wessam Hussein and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Statistical Monitoring of Complex Multivatiate Processes written by Uwe Kruger and published by John Wiley & Sons. This book was released on 2012-08-06 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development and application of multivariate statisticaltechniques in process monitoring has gained substantial interestover the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complexsystems, such techniques have been refined and applied in variousengineering areas, for example mechanical and manufacturing,chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statisticaltechniques lies in its simplicity and adaptability for developingmonitoring applications. In contrast, competitive model,signal or knowledge based techniques showed their potential onlywhenever cost-benefit economics have justified the required effortin developing applications. Statistical Monitoring of Complex Multivariate Processespresents recent advances in statistics based process monitoring,explaining how these processes can now be used in areas such asmechanical and manufacturing engineering for example, in additionto the traditional chemical industry. This book: Contains a detailed theoretical background of the componenttechnology. Brings together a large body of work to address thefield’s drawbacks, and develops methods for theirimprovement. Details cross-disciplinary utilization, exemplified by examplesin chemical, mechanical and manufacturing engineering. Presents real life industrial applications, outliningdeficiencies in the methodology and how to address them. Includes numerous examples, tutorial questions and homeworkassignments in the form of individual and team-based projects, toenhance the learning experience. Features a supplementary website including Matlab algorithmsand data sets. This book provides a timely reference text to the rapidlyevolving area of multivariate statistical analysis for academics,advanced level students, and practitioners alike.

Download or read book Statistical Process Monitoring Using Advanced Data Driven and Deep Learning Approaches written by Fouzi Harrou and published by Elsevier. This book was released on 2020-07-03 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods

Download or read book Dynamic Modeling of Complex Industrial Processes Data driven Methods and Application Research written by Chao Shang and published by Springer. This book was released on 2018-02-22 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts. The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with process data analytics to offer powerful prior knowledge that gives rise to statistical methods tailored to industrial data. It addresses several issues of immediate interest in industrial practice, including process monitoring, control performance assessment and diagnosis, monitoring system design, and product quality prediction. In particular, it proposes a holistic and pragmatic design framework for industrial monitoring systems, which delivers effective elimination of false alarms, as well as intelligent self-running by fully utilizing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industrial process modeling in the era of big data.

Download or read book Gaussian Process Models for Proces Monitoring and Control written by Javier Serradilla and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: One problem of special interest both in industry and the engineering community is that of using the enormous amounts of data routinely generated and recorded in e cient process monitoring and control strategies. In statistical terms this is related to identifying those variables which exhibit unwanted or unusual process variability so that remedial action can be taken. To this end, a common approach in the literature is to reduce the problem dimensionality by using latent variable models. Customarily, the latent variables are a function of all of the original variables and monitoring is carried out in the reduced space. Within this context, this thesis explores the development of models in which the latent factors are a function of a subset, only, of the original observations. By doing that, the advantages of monitoring in a reduced subspace are retained but there there are also additional gains in model interpretability. The idea arises from the sparse representation of the mapping matrix between latent and original variables in a linear factor analysis (FA) model. An extension of principal component analysis (PCA) to monitor nonlinear systems is proposed by using a a Gaussian Process Latent Variable model [Lawrence, 2005], GPLVM, as a starting point. Its application in a process control problem is also introduced. Using a Gaussian process, GP, as the backbone, we de ne a Gaussian Process Functional Factor Analysis model which maps subsets of the latent variables to the observed data-space; a study of the model asymptotic properties is given. Several parameter inference methods as well as a model selection procedure via penalty functions are also proposed. There are several scienti c disciplines involved in the problem at hand. Chemical engineers refer to it as a sub- eld of Process Control known as Multivariate Statistical Process Control. It is also an area of tremendous success in process Chemometrics where it has grown very rapidly over the last two decades. In Statistics, it touches the topics of latent variable models and variable selection methods. And within the Machine Learning community is classi ed as an Unsupervised Learning problem.

Download or read book Machine Learning in Python for Process and Equipment Condition Monitoring and Predictive Maintenance written by Ankur Kumar and published by MLforPSE. This book was released on 2024-01-12 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to help readers quickly gain a working knowledge of machine learning-based techniques that are widely employed for building equipment condition monitoring, plantwide monitoring , and predictive maintenance solutions in process industry . The book covers a broad spectrum of techniques ranging from univariate control charts to deep learning-based prediction of remaining useful life. Consequently, the readers can leverage the concepts learned to build advanced solutions for fault detection, fault diagnosis, and fault prognosis. The application focused approach of the book is reader friendly and easily digestible to the practicing and aspiring process engineers and data scientists. Upon completion, readers will be able to confidently navigate the Prognostics and Health Management literature and make judicious selection of modeling approaches suitable for their problems. This book has been divided into seven parts. Part 1 lays down the basic foundations of ML-assisted process and equipment condition monitoring, and predictive maintenance. Part 2 provides in-detail presentation of classical ML techniques for univariate signal monitoring. Different types of control charts and time-series pattern matching methodologies are discussed. Part 3 is focused on the widely popular multivariate statistical process monitoring (MSPM) techniques. Emphasis is paid to both the fault detection and fault isolation/diagnosis aspects. Part 4 covers the process monitoring applications of classical machine learning techniques such as k-NN, isolation forests, support vector machines, etc. These techniques come in handy for processes that cannot be satisfactorily handled via MSPM techniques. Part 5 navigates the world of artificial neural networks (ANN) and studies the different ANN structures that are commonly employed for fault detection and diagnosis in process industry. Part 6 focusses on vibration-based monitoring of rotating machinery and Part 7 deals with prognostic techniques for predictive maintenance applications. Broadly, the book covers the following: Exploratory analysis of process data Best practices for process monitoring and predictive maintenance solutions Univariate monitoring via control charts and time series data mining Multivariate statistical process monitoring techniques (PCA, PLS, FDA, etc.) Machine learning and deep learning techniques to handle dynamic, nonlinear, and multimodal processes Fault detection and diagnosis of rotating machinery using vibration data Remaining useful life predictions for predictive maintenance

Download or read book PAT Applied in Biopharmaceutical Process Development And Manufacturing written by Cenk Undey and published by CRC Press. This book was released on 2011-12-07 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: As with all of pharmaceutical production, the regulatory environment for the production of therapeutics has been changing as a direct result of the US FDA-initiated Quality by Design (QbD) guidelines and corresponding activities of the International Committee for Harmonization (ICH). Given the rapid growth in the biopharmaceutical area and the comp

Download or read book Advanced Control and Supervision of Mineral Processing Plants written by Daniel Sbárbaro and published by Springer Science & Business Media. This book was released on 2010-08-20 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Control and Supervision of Mineral Processing Plants describes the use of dynamic models of mineral processing equipment in the design of control, data reconciliation and soft-sensing schemes; through examples, it illustrates tools integrating simulation and control system design for comminuting circuits and flotation columns. Coverage is given to the design of soft sensors based on either single-point measurements or more complex measurements like images. Issues concerning data reconciliation and its employment in the creation of instrument architecture and fault diagnosis are surveyed. In consideration of the widespread use of distributed control and information management systems in mineral processing, the book describes the platforms and toolkits available for implementing such systems. Applications of the techniques described in real plants are used to highlight their benefits; information for all of the examples, together with supporting MATLAB® code can be found at www.springer.com/978-1-84996-105-9.

Download or read book Comprehensive Chemometrics written by Steven Brown and published by Elsevier. This book was released on 2020-05-26 with total page 2948 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive Chemometrics, Second Edition, Four Volume Set features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in 2009. Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data fusion and sparse methods. The book follows a similar structure to the previous edition, using the same section titles to frame articles. Many chapters from the previous edition are updated, but there are also many new chapters on the latest developments. Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience

Download or read book Chemical Engineering in the Pharmaceutical Industry written by Mary T. am Ende and published by John Wiley & Sons. This book was released on 2019-04-08 with total page 1435 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the important chemical engineering concepts for the development of new drugs, revised second edition The revised and updated second edition of Chemical Engineering in the Pharmaceutical Industry offers a guide to the experimental and computational methods related to drug product design and development. The second edition has been greatly expanded and covers a range of topics related to formulation design and process development of drug products. The authors review basic analytics for quantitation of drug product quality attributes, such as potency, purity, content uniformity, and dissolution, that are addressed with consideration of the applied statistics, process analytical technology, and process control. The 2nd Edition is divided into two separate books: 1) Active Pharmaceutical Ingredients (API’s) and 2) Drug Product Design, Development and Modeling. The contributors explore technology transfer and scale-up of batch processes that are exemplified experimentally and computationally. Written for engineers working in the field, the book examines in-silico process modeling tools that streamline experimental screening approaches. In addition, the authors discuss the emerging field of continuous drug product manufacturing. This revised second edition: Contains 21 new or revised chapters, including chapters on quality by design, computational approaches for drug product modeling, process design with PAT and process control, engineering challenges and solutions Covers chemistry and engineering activities related to dosage form design, and process development, and scale-up Offers analytical methods and applied statistics that highlight drug product quality attributes as design features Presents updated and new example calculations and associated solutions Includes contributions from leading experts in the field Written for pharmaceutical engineers, chemical engineers, undergraduate and graduation students, and professionals in the field of pharmaceutical sciences and manufacturing, Chemical Engineering in the Pharmaceutical Industry, Second Edition contains information designed to be of use from the engineer's perspective and spans information from solid to semi-solid to lyophilized drug products.

Download or read book Developing Solid Oral Dosage Forms written by Yihong Qiu and published by Academic Press. This book was released on 2016-11-08 with total page 1178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developing Solid Oral Dosage Forms: Pharmaceutical Theory and Practice, Second Edition illustrates how to develop high-quality, safe, and effective pharmaceutical products by discussing the latest techniques, tools, and scientific advances in preformulation investigation, formulation, process design, characterization, scale-up, and production operations. This book covers the essential principles of physical pharmacy, biopharmaceutics, and industrial pharmacy, and their application to the research and development process of oral dosage forms. Chapters have been added, combined, deleted, and completely revised as necessary to produce a comprehensive, well-organized, valuable reference for industry professionals and academics engaged in all aspects of the development process. New and important topics include spray drying, amorphous solid dispersion using hot-melt extrusion, modeling and simulation, bioequivalence of complex modified-released dosage forms, biowaivers, and much more. Written and edited by an international team of leading experts with experience and knowledge across industry, academia, and regulatory settings Includes new chapters covering the pharmaceutical applications of surface phenomenon, predictive biopharmaceutics and pharmacokinetics, the development of formulations for drug discovery support, and much more Presents new case studies throughout, and a section completely devoted to regulatory aspects, including global product regulation and international perspectives

Download or read book Chemical Engineering in the Pharmaceutical Industry written by David J. am Ende and published by John Wiley & Sons. This book was released on 2011-03-10 with total page 1431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with various unique elements in the drug development process within chemical engineering science and pharmaceutical R&D. The book is intended to be used as a professional reference and potentially as a text book reference in pharmaceutical engineering and pharmaceutical sciences. Many of the experimental methods related to pharmaceutical process development are learned on the job. This book is intended to provide many of those important concepts that R&D Engineers and manufacturing Engineers should know and be familiar if they are going to be successful in the Pharmaceutical Industry. These include basic analytics for quantitation of reaction components– often skipped in ChE Reaction Engineering and kinetics books. In addition Chemical Engineering in the Pharmaceutical Industry introduces contemporary methods of data analysis for kinetic modeling and extends these concepts into Quality by Design strategies for regulatory filings. For the current professionals, in-silico process modeling tools that streamline experimental screening approaches is also new and presented here. Continuous flow processing, although mainstream for ChE, is unique in this context given the range of scales and the complex economics associated with transforming existing batch-plant capacity. The book will be split into four distinct yet related parts. These parts will address the fundamentals of analytical techniques for engineers, thermodynamic modeling, and finally provides an appendix with common engineering tools and examples of their applications.

Download or read book Methods to Assess and Manage Process Safety in Digitalized Process System written by Faisal Khan and published by Academic Press. This book was released on 2022-07-06 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods to Assess and Manage Process Safety in Digitalized Process System, Volume Six, the latest release in the Methods in Chemical Process Safety series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Methods in Chemical Process Safety series Provides the authority and expertise of leading contributors from an international board of authors

Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.

Download or read book Functional Statistics written by Javier Martínez Torres and published by MDPI. This book was released on 2020-12-23 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functional analysis, the branch that lies between mathematical analysis and statistics, has many applications in the field of engineering and processes. Thus, this book presents several applications carried out from this perspective, as well as various works of a theoretical nature that take a further step so that researchers can use these models with high precision.

Download or read book Practical Guide to Hot Melt Extrusion written by Mohammed Maniruzzaman and published by Smithers Rapra. This book was released on 2015-07-22 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few decades, hot-melt extrusion (HME) techniques have been shown to exhibit remarkable potential for the manufacture of various pharmaceutical products. HME is an emerging processing technology used primarily for the manufacture of pharmaceutical solid dispersions, combining the advantages of a solvent-free process with fewer production steps making it suitable for easy to scale-up and continuous manufacturing applications. A single unit HME based operation, employing heat and mechanical shear, has displayed a significant potential to retain the stability even of thermo-labile therapeutics e.g., proteins. HME has now explicitly been established from a quality-by-design viewpoint for in-line data monitoring as per the recent guidelines issued by the US Food and Drugs Administration (FDA).This book will focus primarily on the foregoing subject areas and will be of significant interest to a broad/interdisciplinary readership across the industries and academia for, (but not limited to) the following reasons:- Emerging HME processes and applications for multiple drug delivery.- Solid-state engineering, solubility enhancement, controlled release, taste masking and sustained release case studies from a continuous manufacturing view-point.- Means to explore the potential of continuous manufacture of co-crystals for promoting solvent free production methods.- Scale-up case study and issue considerations and studies on the regulatory guidelines (FDA) for continuous manufacturing involving emerging HME techniques.

Download or read book European Symposium on Computer Aided Process Engineering 14 written by Ana Paula Barbosa-Póvoa and published by Elsevier. This book was released on 2004-05-14 with total page 1200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains papers presented at the 14th European Symposium on Computer Aided Process Engineering (ESCAPE-14). The ESCAPE symposia bring together scientists, students and engineers from academia and industry, who are active in the research and application of Computer Aided Process Engineering. The objective of ESCAPE-14 is to highlight the use of computers and information technology tools on five specific themes: 1. Product and Process Design, 2. Synthesis and Process Integration, 3. Process Control and Analysis, 4. Manufacturing & Process Operations, 5. New Challenges in CAPE. - Provides this year's comprehensive overview of the current state of affairs in the CAPE community- Contains reports from the frontiers of science by the field's most respected scientists - Special Keynote by Professor Roger Sargent, Long Term Achievement CAPE Award winner