Statistical and Computational Techniques in Manufacturing

Statistical and Computational Techniques in Manufacturing
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.

Computational Methods for Optimizing Manufacturing Technology: Models and Techniques

Computational Methods for Optimizing Manufacturing Technology: Models and Techniques
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.

Industrial Statistics

Industrial Statistics
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.

Computational Methods for Application in Industry 4.0

Computational Methods for Application in Industry 4.0
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.

Data Analytics, Computational Statistics, and Operations Research for Engineers

Data Analytics, Computational Statistics, and Operations Research for Engineers
Author: Debabrata Samanta
Publisher: CRC Press
Total Pages: 0
Release: 2022-04-05
Genre: Technology & Engineering
ISBN: 100055046X

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

Process Optimization

Process Optimization
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.

Design of Experiments in Production Engineering

Design of Experiments in Production Engineering
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.

Modern Multivariate Statistical Techniques

Modern Multivariate Statistical Techniques
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.

Computational Methods and Production Engineering

Computational Methods and Production Engineering
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