Table Of ContentEvolutionary Optimization of
Material Removal Processes
This text comprehensively focuses on the concepts, implementation, and application of
evolutionary algorithms for predicting, modeling, and optimizing the various material
removal processes from their origin to the current advancements. This one-of-a-kind
book encapsulates all the features related to the application and implementation of
evolutionary algorithms for the purpose of predicting and optimizing the process
characteristics of different machining methods and their allied processes that will
provide comprehensive information. It broadly explains the concepts of employing
evolutionary algorithm-based optimization in a broad domain of various material
removal processes. Therefore, this book will enable prospective readers to take full
advantage of recent findings and advancements in the fields of traditional, advanced,
micro, and hybrid machining, among others. Moreover, the simplicity of its writing will
keep readers engaged throughout and make it easier for them to understand the
advanced topics.
This book
• Offers a step-by-step guide to implement evolutionary algorithms for the
overall optimization of conventional and contemporary machining processes
• Provides in-depth analysis of various material removal processes through
evolutionary optimization
• Details an overview of different evolutionary optimization techniques
• Explores advanced processing of various engineering materials-based case
studies
It further discusses different nature-inspired algorithms-based modeling, prediction,
and modeling of machining responses in attempting advanced machining of the latest
materials and related engineering problems along with case studies and practical
examples. It will be an ideal reference text for graduate students and academic
researchers working in the fields of mechanical engineering, aerospace engineering,
industrial engineering, manufacturing engineering, and materials science.
Evolutionary
Optimization of
Material Removal
Processes
Edited by
Ravi Pratap Singh, Narendra Kumar,
Ravinder Kataria, and Pulak Mohan Pandey
First edition published 2023
by CRC Press
6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742
and by CRC Press
4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
CRC Press is an imprint of Taylor & Francis Group, LLC
© 2023 selection and editorial matter, Ravi Pratap Singh,
Narendra Kumar, Ravinder Kataria and Pulak Mohan Pandey; individual
chapters, the contributors
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Library of Congress Cataloging-in-Publication Data
Names: Singh, Ravi Pratap, editor.
Title: Evolutionary optimization of material removal processes / edited by Ravi
Pratap Singh, Narendra Kumar, Ravinder Kataria, and Pulak Mohan Pandey.
Description: First edition. | Boca Raton : CRC Press, 2023. |
Includes bibliographical references and index.
Identifiers: LCCN 2022035921 (print) | LCCN 2022035922 (ebook) |
ISBN 9781032136516 (hardback) | ISBN 9781032192703 (paperback) |
ISBN 9781003258421 (ebook)
Subjects: LCSH: Machining‐‐Data processing. | Cutting‐‐Data processing. |
Evolutionary computation. | Mathematical optimization.
Classification: LCC TJ1185 .E96 2023 (print) | LCC TJ1185 (ebook) |
DDC 671.3/50285‐‐dc23/eng/20221012
LC record available at https://lccn.loc.gov/2022035921
LC ebook record available at https://lccn.loc.gov/2022035922
ISBN: 978-1-032-13651-6 (hbk)
ISBN: 978-1-032-19270-3 (pbk)
ISBN: 978-1-003-25842-1 (ebk)
DOI: 10.1201/9781003258421
Typeset in Sabon
by MPS Limited, Dehradun
Contents
Acknowledgments ix
Preface xi
Editors xiii
Contributors xvii
Introduction 1
1 Experimental Investigation of Surface Roughness for
Turning of UD-GFRP Composite Using PSO, GSA,
and PSOGSA Techniques 3
MEENU AND SURINDER KUMAR
2 Multi-response Optimization During High-speed Drilling
of Composite Laminate Using Grey Entropy Fuzzy (GEF)
and Entropy-Based Weight Integrated Multi-Variate Loss
Function 23
JALUMEDI BABU, KHALEEL AHMED, LIJO PAUL, ABYSON SCARIA,
AND J. PAULO DAVIM
3 Implementation of Modern Meta-Heuristic Algorithms for
Optimizing Machinability in Dry CNC Finish-Turning of
AISI H13 Die Steel Under Annealed and Hardened States 45
NIKOLAOS A. FOUNTAS, IOANNIS PAPANTONIOU, JOHN KECHAGIAS,
DIMITRIOS E. MANOLAKOS, AND NIKOLAOS M. VAXEVANIDIS
4 Multi-Response Optimization in Turning of UD-GFRP
Composites using Weighted Principal Component
Analysis (WPCA) 61
MEENU AND SURINDER KUMAR
v
vi Contents
5 Processes Parameters Optimization on Surface Roughness
in Turning of E-glass UD-GFRP Composites Using Flower
Pollination Algorithm (FPA) 79
SURINDER KUMAR AND MEENU
6 Application of ANN and Taguchi Technique for Material
Removal Rate by Abrasive Jet Machining with Special
Abrasive Materials 97
SACHIN P. AMBADE, CHETAN K. TEMBHURKAR, SAGAR SHELARE,
AND SANTOSH GUPTA
7 Investigation of MRR in Face Turning Unidirectional GFRP
Composites by Using Multiple Regression Methodology and
an Artificial Neural Network 129
SURINDER KUMAR, MEENU, AND PAWAN KUMAR
8 Optimization of CNC Milling Parameters for Al-CNT
Composites Using an Entropy-Based Neutrosophic Grey
Relational TOPSIS Method 147
SACHCHIDA NAND, MANVANDRA K SINGH, AND C M KRISHNA
9 Experimental Investigation of EDM Potential to Machine
AISI 202 Using a Copper-Alloy Electrode and Its Modelling
by an Artificial Neural Network 167
SUBHASH SINGH AND GIRIJA NANDAN ARKA
10 Prediction and Neural Modeling of Material Removal Rate
in Electrochemical Machining of Nimonic-263 Alloy 183
DILKUSH BAIRWA, DR RAVI PRATAP SINGH, DR RAVINDER KATARIA,
DR RAVI BUTOLA, DR MOHD JAVAID, SHAILENDRA CHAUHAN,
AND MADHUSUDAN PAINULY
11 Optimization of End Milling Process Variables Using a
Multi-Objective Genetic Algorithm 197
JIGNESH GIRISHBHAI PARMAR AND
DR. KOMAL GHANSHYAMBHAI DAVE
Contents vii
12 Micro-Electrochemical Machining of Nimonic 263 Alloy:
An Experimental Investigation and ANN-Based Prediction
of Radial Over Cut 215
DILKUSH BAIRWA, DR RAVI PRATAP SINGH, DR RAVINDER KATARIA,
DR SANDEEP SINGHAL, DR NARENDRA KUMAR, SHAILENDRA CHAUHAN,
AND MADHUSUDAN PAINULY
Index 229
Acknowledgments
This book volume focuses in detail on the concepts, implementation, and
application of evolutionary algorithms for predicting, modeling, and
optimizing the various material removal processes from their origin to the
current advancements. We owe many thanks to all the people who helped
and supported us for the completion of this book project on time. We, the
editors of this book, would like to express our gratitude towards all the
esteemed authors for contributing their valuable research articles for this
book. We would also like to acknowledge the reviewers for their
painstaking and time-consuming effort in reviewing the chapters and
providing their thorough evaluations for improving the quality.
We would further would like to express our sincere gratitude towards the
entire team of CRC Press, Taylor & Francis Group who have given us time
and space to write this book, in particular Gauravjeet Singh Reen, Senior
Commissioning Editor, CRC Press for his continuous support and valuable
guidance in completing this book proposal with this success. We would also
like to express our sincere gratitude towards, Prof V K Jain, IIT Kanpur;
Prof Pradeep Kumar, IIT Roorkee; and Prof Sandeep Singhal, NIT
Kurukshetra, for their motivation and valuable inputs from time to time.
Lastly, we would like to thank to our families for believing in us and
encouraging us to be the best we can be, and our friends, colleagues, and
scholars for always being there with a helping hand and a good laugh.
ix
