[PDF] Statistical And Computational Techniques In Manufacturing eBook

Author : J. Paulo Davim
Publisher : Springer Science & Business Media
Page : 294 pages
File Size : 29,42 MB
Release : 2012-03-06
Category : Technology & Engineering
ISBN : 364225859X

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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 : Nikolaos E. Karkalos
Publisher : Springer
Page : 74 pages
File Size : 47,53 MB
Release : 2018-05-21
Category : Technology & Engineering
ISBN : 3319923935

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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 : Debabrata Samanta
Publisher : CRC Press
Page : 275 pages
File Size : 35,43 MB
Release : 2022-03-24
Category : Computers
ISBN : 1000550427

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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.

Author : Davim, J. Paulo
Publisher : IGI Global
Page : 464 pages
File Size : 24,6 MB
Release : 2012-02-29
Category : Technology & Engineering
ISBN : 1466601299

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"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 : Enrico Zio
Publisher : World Scientific
Page : 363 pages
File Size : 29,59 MB
Release : 2009
Category : Technology & Engineering
ISBN : 9812839011

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This book illustrates a number of modelling and computational techniques for addressing relevant issues in reliability and risk analysis. In particular, it provides: i) a basic illustration of some methods used in reliability and risk analysis for modelling the stochastic failure and repair behaviour of systems, e.g. the Markov and Monte Carlo simulation methods; ii) an introduction to Genetic Algorithms, tailored to their application for RAMS (Reliability, Availability, Maintainability and Safety) optimization; iii) an introduction to key issues of system reliability and risk analysis, like dependent failures and importance measures; and iv) a presentation of the issue of uncertainty and of the techniques of sensitivity and uncertainty analysis used in support of reliability and risk analysis.The book provides a technical basis for senior undergraduate or graduate courses and a reference for researchers and practitioners in the field of reliability and risk analysis. Several practical examples are included to demonstrate the application of the concepts and techniques in practice.

Author :
Publisher :
Page : 325 pages
File Size : 32,10 MB
Release : 2020
Category : Computer systems
ISBN : 9783030434137

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This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.

Author : Hoang Pham
Publisher : Springer Nature
Page : 325 pages
File Size : 49,73 MB
Release : 2020-03-28
Category : Technology & Engineering
ISBN : 3030434125

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This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.

Author : R. Ganesh Narayanan
Publisher : Springer Nature
Page : 1092 pages
File Size : 22,15 MB
Release : 2019-10-17
Category : Technology & Engineering
ISBN : 9813290722

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This volume presents a selection of papers from the 2nd International Conference on Computational Methods in Manufacturing (ICCMM 2019). The papers cover the recent advances in computational methods for simulating various manufacturing processes like machining, laser welding, laser bending, strip rolling, surface characterization and measurement. Articles in this volume discuss both the development of new methods and the application and efficacy of existing computational methods in manufacturing sector. This volume will be of interest to researchers in both industry and academia working on computational methods in manufacturing.

Author : Alan J. Izenman
Publisher : Springer Science & Business Media
Page : 757 pages
File Size : 28,4 MB
Release : 2009-03-02
Category : Mathematics
ISBN : 0387781897

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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 : Stanley B. Gershwin
Publisher : Springer Science & Business Media
Page : 443 pages
File Size : 18,68 MB
Release : 2012-12-06
Category : Business & Economics
ISBN : 1461510198

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Analysis and Modeling of Manufacturing Systems is a set of papers on some of the newest research and applications of mathematical and computational techniques to manufacturing systems and supply chains. These papers deal with fundamental questions (how to predict factory performance: how to operate production systems) and explicitly treat the stochastic nature of failures, operation times, demand, and other important events. Analysis and Modeling of Manufacturing Systems will be of interest to readers with a strong background in operations research, including researchers and mathematically sophisticated practitioners.