Computer Science & Information Management

Intelligent Machining
Using Computational Intelligence to Optimize Manufacturing Processes

Editors: Kanak Kalita, PhD
Ranjan Kumar Ghadai, PhD
Xiao-Zhi Gao, PhD

Intelligent Machining

In Production
Pub Date: Forthcoming January 2025
Hardback Price: $190 US | £150 UK
Hard ISBN: 9781774919583
Pages: Est. 225pp w/index
Binding Type: Hardback / ebook
Notes: 14 color and 73 b/w illustrations


Reviews
“Meticulous . . . The journey from understanding the potential of high-strength steel sections to the intricacies of CNC lathe selection using advanced methods provides a multi-faceted perspective. The chapters on fabrication techniques, composite coatings, and robotic navigation underscore the blend of theoretical insights with practical applications ensure that readers get a holistic understanding. . . . A beacon for those charting the future of intelligent machining. As you delve into its pages, I hope you share the same excitement, curiosity, and optimism I felt. The future of manufacturing is bright, and this volume shines a spotlight on its myriad possibilities.”
—From the Foreword by Prof. Dr. Robert Cep, VSB-Technical University of Ostrava, Czech Republic



Manufacturing, as an industry, has been undergoing huge transformation in recent times due to technological development, putting manufacturing at the intersection of traditional techniques and advanced computational intelligence. This new volume, Intelligent Machining: Using Computational Intelligence to Optimize Manufacturing Processes, provides an understanding of the nuances of this transformation.

The book begins with an exploration into the realm of high-strength steel sections, charting their importance and utility. It further goes on to elucidate the selection of a CNC lathe using the TOPSIS method. Bibliometric insights into multi-objective optimization and metaheuristic algorithms are also discussed as is the development of high entropy alloys. The book delves into practical applications of computational intelligence, including optimizing investment casting process parameters, enhancing mobile robot navigation performance, and more. The intricate processes behind fabrication is also explored along with a study of wear and thermal behaviors of advanced composite coatings.

The concluding chapters further discuss the merging of computational techniques and traditional processes. Chapters include topics ranging from the fabrication of lightweight aluminum-based magnetic metals to the cutting-edge use of the artificial bee colony (ABC) algorithm in laser welding.

Painting a comprehensive picture of the state-of-the-art advancements and methodologies that are reshaping the manufacturing world, this book will be valuable to seasoned industry professionals, academic researchers, and even students new to the world of intelligent machining.

CONTENTS:
Foreword by Robert Cep

Preface

Introduction

1. Usefulness of High Strength Steel Sections as Compressive Members

Asim Kumar Samanta, Kishore Debnath, and Arpan Kumar Mondal

2. Selection of a CNC Lathe by the TOPSIS Method Under an MCDM Environment Using MATLAB
Ayan Polley, Sandipan Das, Debal Pramanik, Nilanjan Roy, Arindam Chakraborty, and Koushik Mishra

3. Bibliometric Analysis on Multi-Objective Optimization and Metaheuristic Algorithm
Saibal Kumar Saha and Sunny Diyaley

4. Development of High Entropy Alloy: A Review
Anubhav Banerjee and Arpan Kumar Mondal

5. Optimization of Investment Casting Process Parameters of Hydraulic Flange Using Artificial Neural Network Technique
Suraj S. Kumar, Bharatish A., Akshay Bhagavath, Suhas D., Shashank M., and G. R. Rajkumar

6. Enhancing Mobile Robot Navigation Performance with Deep Deterministic Policy-Gradient Algorithm: A Simulation-Based Investigation
Muhammad Faqiihuddin Bin Nasary and Azhar Mohd Ibrahim

7. Fabrication of Burr-Free Micro Edge on SS-304 Using Al 2O 3 and SiC Abrasives
Mriganka Maity, Joydip Kumar Mondal, and Somnath Das

8. Wear and Thermal Behaviors of Micro- and Nano-Filler-Based Solvent Free Epoxy-Phenalkamine Composite Coatings
Ujjwal Ghosh, Sourav Debnath, Buddhadeb Duari, Kaushik Duari, Totan Roy, and Akshay Kumar Pramanick

9. Fabrication and Study on Light Weight Aluminum Based Magnetic Metal
Samrat Paul, Sourav Debnath, and Akshay Kumar Pramanick

10. Experimental Investigation and Optimization of Laser Welding of AA2024 with Artificial Bee Colony Algorithm
Upama Dey and Souren Mitra

11. Development of Mold Filling Time for Metal Casting Using Kinetic Energy Correction Factor
Soumyajit Roy, Sourav Debnath, Akshay Kumar Pramanick, and Prasanta Kumar Datta

12. Effect of Heat Input and Torch Position on Al 6061 to Coated Steel Dissimilar Joining by CMT for Car Body Structure
Ankush Khansole, Kanwer S. Arora, and Sushovan Basak

13. Forming of Ceramic Composites: State-of-the-Art and Future Perspectives
Kanak Kalita, G. Shanmugasundar, Jasgurpreet Singh Chohan, and Shankar Chakraborty

Index


About the Authors / Editors:
Editors: Kanak Kalita, PhD
Associate Professor, Department of Mechanical Engineering, Vel Tech University, Chennai, India

Kanak Kalita, PhD, is a prominent professor and researcher in mechanical engineering, acknowledged among the Top 2% Scientists Worldwide 2023 by Stanford University. He currently holds the position of Associate Professor in the Department of Mechanical Engineering at Vel Tech University, Chennai. Dr. Kalita’s scholarly output is both prolific and impactful, as evidenced by his authorship of over 75+ SCI and 125+ SCOPUS articles. His editorial expertise is also notable, having edited eight book volumes. He serves on the editorial boards of several esteemed journals such as Scientific Reports, Frontiers in Mechanical Engineering, and the SAE International Journal of Materials and Manufacturing. His guest editorship for numerous journals further demonstrates his commitment to advancing scholarly discourse in his field. His work is highly regarded in the academic community, as reflected by his impressive 1800+ citations and an h-index of 24. Dr. Kalita is an engaging speaker, having delivered over 20 expert lectures across various academic and professional platforms. He has successfully guided eight undergraduate and four postgraduate students and is currently supervising four PhD candidates. His research interests include machine learning, fuzzy decision making, metamodeling, process optimization, the finite element method, and composites. He earned both his ME and PhD in Applied Mechanics from the Indian Institute of Engineering, Science & Technology, Shibpur, India, in 2014 and 2019 respectively.

Ranjan Kumar Ghadai, PhD
Associate Professor, Mechanical and Industrial Engineering Department, Manipal Institute of Technology, MAHE, Manipal, India

Ranjan Kumar Ghadai, PhD, is a distinguished academician with extensive research experience in the field of materials science and nanotechnology. He holds MTech and PhD degrees in Mechanical Engineering from the Indian Institute of Engineering, Science & Technology, Shibpur, India, along with a B. Tech in Mechanical Engineering from Biju Patnaik University of Technology, Odisha, India. He has over 10 years of teaching and research experience. Currently, he is working as an Associate professor in the Mechanical and Industrial Engineering Department of Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India. He has published more than 75 SCI/Scopus-indexed research articles. His broad research area includes thin film coating deposition, process optimization, and development of composites. Currently, he is handling two sponsored projects as PI and one as Co-PI. His current h?index is 22, and his i10 index is 33. He has guided three postgraduate students and is currently guiding five PhD scholars. Also, he is the reviewer for many peer-reviewed journals like Robotics and Computer-Integrated Manufacturing, Scientific Reports, Advances in Manufacturing, Surface and Interface, Materials Chemistry and Physics etc. He has given talks in many conferences and workshops as a resource person. He is the Associate Editor of Frontier in Mechanical Engineering. He has edited four books and four conference proceedings.

Xiao-Zhi Gao, PhD
Professor, University of Eastern Finland, Kuopio, Finland

Xiao-Zhi Gao, PhD, is an esteemed academic with an extensive background in technology and computing. With over 22 years of experience in teaching and research, Dr. Gao has established himself as a leading figure in the field. Since 2018, he has been a Professor at the University of Eastern Finland, Kuopio, Finland, where he continues to contribute significantly to the academic community. Dr. Gao serves as chief editor, associate editor, and a member of the editorial board for several prominent soft computing journals, including Swarm and Evolutionary Computation, Information Sciences, and Applied Soft Computing. His scholarly output is impressive, with over 500 technical papers published in refereed journals and international conferences and more than 400 SCI/SCOPUS research articles to his name. In addition to his extensive list of articles, Dr. Gao has authored two books and edited four books for renowned publishers such as Springer and IGI Global. His research is particularly focused on nature-inspired computing methods, with applications spanning optimization, prediction, data mining, signal processing, control, and industrial electronics. This breadth of interest underscores his deep understanding and innovative approach to complex technological challenges. Dr. Gao’s academic achievements are further highlighted by his impressive Google Scholar H-index of 42, reflecting the widespread influence and high citation rate of his work. He commenced his academic journey at Harbin Institute of Technology, China, where he earned both his BSc and MSc degrees. Dr. Gao further advanced his education at the Helsinki University of Technology, now known as Aalto University, Finland, where he obtained his PhD in 1999.




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