Optimization of Advanced Manufacturing Processes
1st Edition
Published on 29. November 2024
Book
Hardback
262 pages
978-1-77491-602-5 (ISBN)
Description
Optimization for advanced manufacturing processes in fabrication is becoming increasingly important around the world across a range of industries because of its improved productivity, capabilities, efficacy, and sustainability characteristics.
This new book explains how to optimize various industrial systems and processes utilizing new significant statistical and evolutionary methodologies. Statistical, multi-criteria decision-making, and evolutionary strategies for single- and multi-objective optimization are covered here, with relevant theoretical details, salient characteristics, implementation processes, effectiveness studies, and results in manufacturing.
The chapters present a variety of advanced manufacturing processes and optimization techniques. Processes are described with basic explanations, characteristics, and applications in various technological and biomedical domains. The chapters address the processes prediction of mechanical properties, design and development of tools, impact of power supply, increasing machining precision and efficiency, genetic algorithm optimization, additive manufacturing, and much more.
Providing a comprehensive study of advanced manufacturing processes, this volume is a valuable reference for engineers and R&D researchers involved in optimization for advanced manufacturing processes as well as for academics and postgraduate-level students in mechanical engineering, manufacturing engineering, and machining processes.
This new book explains how to optimize various industrial systems and processes utilizing new significant statistical and evolutionary methodologies. Statistical, multi-criteria decision-making, and evolutionary strategies for single- and multi-objective optimization are covered here, with relevant theoretical details, salient characteristics, implementation processes, effectiveness studies, and results in manufacturing.
The chapters present a variety of advanced manufacturing processes and optimization techniques. Processes are described with basic explanations, characteristics, and applications in various technological and biomedical domains. The chapters address the processes prediction of mechanical properties, design and development of tools, impact of power supply, increasing machining precision and efficiency, genetic algorithm optimization, additive manufacturing, and much more.
Providing a comprehensive study of advanced manufacturing processes, this volume is a valuable reference for engineers and R&D researchers involved in optimization for advanced manufacturing processes as well as for academics and postgraduate-level students in mechanical engineering, manufacturing engineering, and machining processes.
More details
Language
English
Place of publication
Oakville
Canada
Target group
College/higher education
Professional and scholarly
Academic and Postgraduate
Illustrations
84 s/w Zeichnungen, 102 s/w Abbildungen, 18 s/w Photographien bzw. Rasterbilder, 7 Farbfotos bzw. farbige Rasterbilder, 15 farbige Abbildungen, 8 farbige Zeichnungen, 85 s/w Tabellen
85 Tables, black and white; 8 Line drawings, color; 84 Line drawings, black and white; 7 Halftones, color; 18 Halftones, black and white; 15 Illustrations, color; 102 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 20 mm
Weight
596 gr
ISBN-13
978-1-77491-602-5 (9781774916025)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Sandip Kunar | Prasenjit Chatterjee | M. Sreenivas Reddy
Optimization of Advanced Manufacturing Processes
E-Book
11/2024
1st Edition
Apple Academic Press Inc.
€198.99
Available for download
Sandip Kunar | Prasenjit Chatterjee | M. Sreenivas Reddy
Optimization of Advanced Manufacturing Processes
E-Book
11/2024
1st Edition
Apple Academic Press Inc.
€198.99
Available for download
Persons
Sandip Kunar, PhD, is Assistant Professor of Mechanical Engineering at Aditya Engineering College, India. He has carried out his research work at the Saha Institute of Nuclear Physics, Kolkata, and Raja Ramanna Centre for Advanced Technology, Bhabha Atomic Research Centre, India. He has published research papers in journals and conference proceedings, book chapters, and 12 books with international book publishers. He has published one international webinar and has filed two patents. Dr. Kunar has received best innovative paper awards at international conferences and was awarded several scholarships. He is a reviewer for several highly reputed international journals and delivers lectures at faculty development programs, short-term courses, workshops, and seminars.
Prasenjit Chatterjee, PhD, is Professor of Mechanical Engineering and Dean (Research and Consultancy), MCKV Institute of Engineering, West Bengal, India. A prolific author and editor, Dr. Chatterjee is the Editor-in-Chief of the Journal of Decision Analytics and Intelligent Computing and guest edited several journal issues. He is also Series Editor of several book series, including Smart and Intelligent Computing in Engineering; Concise Introductions to AI and Data Science; AAP Research Notes on Optimization and Decision-Making Theories; Frontiers of Mechanical and Industrial Engineering; and River Publishers Series in Industrial Manufacturing and Systems Engineering. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods: Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).
M. Sreenivas Reddy, PhD, is Director of the Aditya Group of Educational Institutions, Surampalem, Andhra Pradesh, India, where he is also Principal of Aditya Engineering College. He has more than 20 years of teaching experience and five years of industry experience. His research interests include nonconventional machining processes, manufacturing technology, etc. He has published more than 25 research papers in international journals and conference proceedings as well as several books and book chapters. He has filed 11 patents and is a reviewer of more than ten highly reputed international journals.
Prasenjit Chatterjee, PhD, is Professor of Mechanical Engineering and Dean (Research and Consultancy), MCKV Institute of Engineering, West Bengal, India. A prolific author and editor, Dr. Chatterjee is the Editor-in-Chief of the Journal of Decision Analytics and Intelligent Computing and guest edited several journal issues. He is also Series Editor of several book series, including Smart and Intelligent Computing in Engineering; Concise Introductions to AI and Data Science; AAP Research Notes on Optimization and Decision-Making Theories; Frontiers of Mechanical and Industrial Engineering; and River Publishers Series in Industrial Manufacturing and Systems Engineering. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods: Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).
M. Sreenivas Reddy, PhD, is Director of the Aditya Group of Educational Institutions, Surampalem, Andhra Pradesh, India, where he is also Principal of Aditya Engineering College. He has more than 20 years of teaching experience and five years of industry experience. His research interests include nonconventional machining processes, manufacturing technology, etc. He has published more than 25 research papers in international journals and conference proceedings as well as several books and book chapters. He has filed 11 patents and is a reviewer of more than ten highly reputed international journals.
Content
1. Introduction to Advanced Manufacturing Processes and Optimization Techniques 2. Modeling of Process Parameters for Electrical Discharge Face Grinding Process 3. An ISM-AHP Integrated Approach to Prioritizing Factors for the Implementation of Green Value Stream Mapping 4. Experimental Investigation on AISI D2 during Machining by Graphite Electrode in Electric Discharge Machine 5. Multi-Objective Process Parameter Optimization in Single Point Incremental Forming of SS-304 Using Box-Behnken Design of Experiment and TOPSIS Optimization 6. Optimization and Process Parameters Study in Single Point Incremental Forming of Ti Grade 3 Using Taguchi Design of Experiments and Genetic Algorithm Optimization 7. Multi-Objective Process Parameters Optimization in Single Point Incremental Forming of C110 By Central Composite Design and MOORA Optimization Technique 8. Prediction of Mechanical Properties on Wire Arc Additive Manufacturing 316l Stainless Steel Using Fuzzy Logic 9. Application of Taguchi Coupled with Overall Evolution Criteria in Friction Stir Welding Process for Process Parameters Optimization 10. Recent Developments and Optimization in Additive Manufacturing of Aluminum Alloys 11. Experimental Investigation and Optimization of Metal-Cutting Parameters on Surface Roughness During Hard Turning of A-I-S-I 1043 Steel 12. Modeling and Optimization of Deformation Load in Warm Continuous Extrusion Process 13. Optimization of E-Pulse of WEDM Parameters on Ti-10V-2Fe-3Al Alloy by Gray Relational Analysis for Improving the Surface Integrity 14. Optimization of Wire EDM Process Parameters for EN-31 Steel