Explores high-strength steel sections, charting their importance and utility. Provides bibliometric insights into multi-objective optimization and metaheuristic algorithms. Covers development of high entropy alloys.
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 offers an understanding of the nuances of this transformation. It provides an exploration of high-strength steel sections and discusses 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 are also explored along with a study of wear and thermal behaviors of advanced composite coatings.
1. Usefulness of High-Strength Steel Sections as Compressive Members
2.
Selection of a CNC Lathe by TOPSIS (Technique for Order of Preference by
Similarity to Ideal Solution) Method Under an MCDM (Multi-Criteria Decision
Making) Environment Using MATLAB
3. Bibliometric Analysis on Multiobjective
Optimization and Metaheuristic Algorithm
4. Development of High Entropy
Alloy: A Review
5. Optimization of Investment Casting Process Parameters of
Hydraulic Flange Using Artificial Neural Network Technique
6. Enhancing
Mobile Robot Navigation Performance with a Deep Deterministic Policy-Gradient
Algorithm: A Simulation-Based Investigation
7. Fabrication of Burr-Free Micro
Edge on SS-304 Using Al2O3 and SiC Abrasives
8. Wear and Thermal Behaviors of
Micro and Nanofiller-Based Solvent-Free Epoxy-Phenalkamine Composite Coatings
9. Fabrication and Study on Lightweight Aluminum-Based Magnetic Metal
10.
Experimental Investigation and Optimization of Laser Welding of AA2024 with
an Artificial Bee Colony Algorithm
11. Development of Mold Filling Time for
Metal Casting Using a Kinetic Energy Correction Factor
12. Effect of Heat
Input and Torch Position on Al 6061 to Coated Steel Dissimilar Joining by CMT
for Car Body Structure
13. Forming of Ceramic Composites: State-of-the-Art
and Future Perspectives
Kanak Kalita, PhD, is an Associate Professor of Mechanical Engineering at Vel Tech University, Chennai, India. A prolific author and editor, he is listed among the Top 2% Scientists Worldwide 2023 by Stanford University. Dr. Kalita is an engaging speaker, having delivered expert lectures across various academic and professional platforms. His research interests include machine learning, fuzzy decision making, metamodeling, process optimization, the finite element method, and composites. Ranjan Kumar Ghadai, PhD, is an Associate Professor of Mechanical and Industrial Engineering at the Manipal Institute of Technology, India. He has published more than 75 SCI/Scopus-indexed research articles and is a reviewer for several journals. He is also handling sponsored projects as principal or coprincipal investigator. His broad research area includes thin film coating deposition, process optimization, and development of composites. Xiao-Zhi Gao, PhD, has been a Professor at the University of Eastern Finland, Kuopio, since 2018. Dr. Gao serves as chief editor, associate editor, and a member of the editorial boards for several prominent soft computing journals. He has published over 500 technical papers and over 400 research articles as well as two authored books and several edited books. His research is focused on nature-inspired computing methods, with applications spanning optimization, prediction, data mining, signal processing, control, and industrial electronics.
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