Statistical And Computational Techniques In Manufacturing
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| Author | : J. Paulo Davim |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 294 |
| Release | : 2012-03-06 |
| Genre | : Technology & Engineering |
| ISBN | : 364225859X |
In recent years, interest in developing statistical and computational techniques for applied manufacturing engineering has been increased. Today, due to the great complexity of manufacturing engineering and the high number of parameters used, conventional approaches are no longer sufficient. Therefore, in manufacturing, statistical and computational techniques have achieved several applications, namely, modelling and simulation manufacturing processes, optimization manufacturing parameters, monitoring and control, computer-aided process planning, etc. The present book aims to provide recent information on statistical and computational techniques applied in manufacturing engineering. The content is suitable for final undergraduate engineering courses or as a subject on manufacturing at the postgraduate level. This book serves as a useful reference for academics, statistical and computational science researchers, mechanical, manufacturing and industrial engineers, and professionals in industries related to manufacturing engineering.
| Author | : Davim, J. Paulo |
| Publisher | : IGI Global |
| Total Pages | : 464 |
| Release | : 2012-02-29 |
| Genre | : Technology & Engineering |
| ISBN | : 1466601299 |
"This book contains the latest research developments in manufacturing technology and its optimization, and demonstrates the fundamentals of new computational approaches and the range of their potential application"--Provided by publisher.
| Author | : Nikolaos E. Karkalos |
| Publisher | : Springer |
| Total Pages | : 74 |
| Release | : 2018-05-21 |
| Genre | : Technology & Engineering |
| ISBN | : 3319923935 |
This book presents computational and statistical methods used by intelligent systems within the concept of Industry 4.0. The methods include among others evolution-based and swarm intelligence-based methods. Each method is explained in its fundamental aspects, while some notable bibliography is provided for further reading. This book describes each methods' principles and compares them. It is intended for researchers who are new in computational and statistical methods but also to experienced users.
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 149 |
| Release | : 2016-12-21 |
| Genre | : Technology & Engineering |
| ISBN | : 0309449758 |
Additive manufacturing (AM) methods have great potential for promoting transformative research in many fields across the vast spectrum of engineering and materials science. AM is one of the leading forms of advanced manufacturing which enables direct computer-aided design (CAD) to part production without part-specific tooling. In October 2015 the National Academies of Sciences, Engineering, and Medicine convened a workshop of experts from diverse communities to examine predictive theoretical and computational approaches for various AM technologies. While experimental workshops in AM have been held in the past, this workshop uniquely focused on theoretical and computational approaches and involved areas such as simulation-based engineering and science, integrated computational materials engineering, mechanics, materials science, manufacturing processes, and other specialized areas. This publication summarizes the presentations and discussions from the workshop.
| Author | : Anand M. Joglekar |
| Publisher | : John Wiley & Sons |
| Total Pages | : 283 |
| Release | : 2010-04-30 |
| Genre | : Science |
| ISBN | : 0470584122 |
HELPS YOU FULLY LEVERAGE STATISTICAL METHODS TO IMPROVE INDUSTRIAL PERFORMANCE Industrial Statistics guides you through ten practical statistical methods that have broad applications in many different industries for enhancing research, product design, process design, validation, manufacturing, and continuous improvement. As you progress through the book, you'll discover some valuable methods that are currently underutilized in industry as well as other methods that are often not used correctly. With twenty-five years of teaching and consulting experience, author Anand Joglekar has helped a diverse group of companies reduce costs, accelerate product development, and improve operations through the effective implementation of statistical methods. Based on his experience working with both clients and students, Dr. Joglekar focuses on real-world problem-solving. For each statistical method, the book: Presents the most important underlying concepts clearly and succinctly Minimizes mathematical details that can be delegated to a computer Illustrates applications with numerous practical examples Offers a "Questions to Ask" section at the end of each chapter to assist you with implementation The last chapter consists of 100 practical questions followed by their answers. If you're already familiar with statistical methods, you may want to take the test first to determine which methods to focus on. By helping readers fully leverage statistical methods to improve industrial performance, this book becomes an ideal reference and self-study guide for scientists, engineers, managers and other technical professionals across a wide range of industries. In addition, its clear explanations and examples make it highly suited as a textbook for undergraduate and graduate courses in statistics.
| Author | : Enrique del Castillo |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 462 |
| Release | : 2007-09-14 |
| Genre | : Mathematics |
| ISBN | : 0387714359 |
This book covers several bases at once. It is useful as a textbook for a second course in experimental optimization techniques for industrial production processes. In addition, it is a superb reference volume for use by professors and graduate students in Industrial Engineering and Statistics departments. It will also be of huge interest to applied statisticians, process engineers, and quality engineers working in the electronics and biotech manufacturing industries. In all, it provides an in-depth presentation of the statistical issues that arise in optimization problems, including confidence regions on the optimal settings of a process, stopping rules in experimental optimization, and more.
| Author | : J. Paulo Davim |
| Publisher | : Springer |
| Total Pages | : 201 |
| Release | : 2015-11-06 |
| Genre | : Technology & Engineering |
| ISBN | : 3319238388 |
This book covers design of experiments (DoE) applied in production engineering as a combination of manufacturing technology with applied management science. It presents recent research advances and applications of design experiments in production engineering and the chapters cover metal cutting tools, soft computing for modelling and optmization of machining, waterjet machining of high performance ceramics, among others.
| Author | : Alan J. Izenman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 757 |
| Release | : 2009-03-02 |
| Genre | : Mathematics |
| ISBN | : 0387781897 |
This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.
| Author | : J. Paulo Davim |
| Publisher | : Woodhead Publishing |
| Total Pages | : 244 |
| Release | : 2017-05-25 |
| Genre | : Business & Economics |
| ISBN | : 0857094823 |
Computational Methods and Production Engineering: Research and Development is an original book publishing refereed, high quality articles with a special emphasis on research and development in production engineering and production organization for modern industry. Innovation and the relationship between computational methods and production engineering are presented. Contents include: Finite Element method (FEM) modeling/simulation; Artificial neural networks (ANNs); Genetic algorithms; Evolutionary computation; Fuzzy logic; neuro-fuzzy systems; Particle swarm optimization (PSO); Tabu search and simulation annealing; and optimization techniques for complex systems. As computational methods currently have several applications, including modeling manufacturing processes, monitoring and control, parameters optimization and computer-aided process planning, this book is an ideal resource for practitioners. - Presents cutting-edge computational methods for production engineering - Explores the relationship between applied computational methods and production engineering - Presents new innovations in the field - Edited by a key researcher in the field
| Author | : Thomas P. Ryan |
| Publisher | : John Wiley & Sons |
| Total Pages | : 578 |
| Release | : 2011-09-20 |
| Genre | : Technology & Engineering |
| ISBN | : 1118058100 |
Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
