Details

Statistical and Computational Techniques in Manufacturing


Statistical and Computational Techniques in Manufacturing



von: J. Paulo Davim

96,29 €

Verlag: Springer
Format: PDF
Veröffentl.: 06.03.2012
ISBN/EAN: 9783642258596
Sprache: englisch
Anzahl Seiten: 286

Dieses eBook enthält ein Wasserzeichen.

Beschreibungen

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.
<p>Machining.- Non traditional machining (EDM, LAM, USM, etc).-Abrasive machining.- Casting &amp; joining.- Forming.- Powder metallurgy.- Composites &amp; ceramics processing.- Rapid prototyping &amp; tooling processes.- Micro and nanomanufacturing processes.- Sustainable and green manufacturing.- Manufacturing systems.- Statistical and computational techniques.- Design experiments.- Taguchi techniques.- ANOVA (Analysis of variance).- MRA (multi analysis regression).- RSM (Response surface methodology) Finite Element Method (FEM) modeling/simulation.- Artificial Neural Networks (ANNs).- Evolutionary computation.- Fuzzy logic.- Neuro-fuzzy systems.- Particle swarm optimization (PSO).- Optimization techniques of complex systems.</p>
<p>J. Paulo Davim received his PhD degree in Mechanical Engineering from the University of Porto in 1997 and the Aggregation from the University of Coimbra in 2005. Between 1986/96, he was a lecturer at the University of Porto. Currently, he is an Aggregate Professor at the Department of Mechanical Engineering of the University of Aveiro and the Head of MACTRIB - Machining and Tribology Research Group</p><p>http://www2.mec.ua.pt/machining . He has over 24 years of teaching and research experience in manufacturing, materials and mechanical engineering, with special emphasis in Machining &amp; Tribology. He is the Editor-in-Chief of six international journals, Guest Editor of journals, books Editor, book Series Editor and Scientific Advisory for many</p><p>international journals and conferences. Presently, he is an Editorial Board member of 15 international journals and reviewer for than 50 prestigious ISI web Science journals. In addition, he has also authored and co-authored more than 20 book chapters and 300 articles in journals and </p><p>conferences (more 150 articles in ISI Web Science, h-index 16).</p><p>Personal Web page:</p><p>http://www2.mec.ua.pt/machining/pers-davim.htm</p><p>Publications:</p><p>http://www2.mec.ua.pt/machining/Publications_Mactrib.htm</p>
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.
<p>Chapters written by experts in the field</p><p>Useful for teaching modern manufacturing</p><p>Reference work for both students and industrial engineers</p>

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