Table Of Content

Evolutionary 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 Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www.copyright.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. For works that are not available on CCC please contact [email protected] Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. 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