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Erschienen in:
Screening (Sieve) Design of Experiments in Metal Cutting Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Modelling and Optimization of Machining with the Use of Statistical Methods and Soft Computing

verfasst von : Angelos P. Markopoulos, Witold Habrat, Nikolaos I. Galanis, Nikolaos E. Karkalos

Erschienen in: Design of Experiments in Production Engineering

Verlag: Springer International Publishing

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Abstract

This book chapter pertains to the use of statistical methods and soft computing techniques that can be used in the modelling and optimization of machining processes. More specifically, the factorial design method, Taguchi method, response surface methodology (RSM), analysis of variance, grey relational analysis (GRA), statistical regression methods, artificial neural networks (ANN), fuzzy logic and genetic algorithms are thoroughly examined. As part of the design of experiments (DOE) the aforementioned methods and techniques have proven to be very powerful and reliable tools. Especially in machining, a plethora of works have already been published indicating the importance of these methods.

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Vorheriges Kapitel Screening (Sieve) Design of Experiments in Metal Cutting
Nächstes Kapitel Design of Experiments—Statistical and Artificial Intelligence Analysis for the Improvement of Machining Processes: A Review
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Metadaten
Titel
Modelling and Optimization of Machining with the Use of Statistical Methods and Soft Computing
verfasst von
Angelos P. Markopoulos
Witold Habrat
Nikolaos I. Galanis
Nikolaos E. Karkalos
Copyright-Jahr
2016
Buch
Design of Experiments in Production Engineering

Print ISBN: 978-3-319-23837-1

Electronic ISBN: 978-3-319-23838-8

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-23838-8_2

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