Buch, Englisch, 224 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g
Buch, Englisch, 224 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g
Reihe: Advanced Materials Processing and Manufacturing
ISBN: 978-1-032-58189-7
Verlag: Taylor & Francis Ltd
This book covers modeling and optimization of various modern manufacturing processes such as advanced machining, hybrid manufacturing, and additive manufacturing including related case studies in these domains. Various areas like smart manufacturing, hybrid manufacturing, 3D printing, process modeling and characterization, optimization, and so forth are covered in detail. Focus of this book is on Artificial neural network, finite element analysis, firefly/genetic algorithm, particle swarm, fuzzy-based techniques, are the main optimization and modeling techniques.
Features:
- Provides in-depth investigations on prospects of modeling and optimization of modern manufacturing processes.
- Detailed overview on different evolutionary and bio-inspired optimization techniques and their implementation.
- Explains step by step guide to use Machine Learning for the enhancement of productivity and quality in modern manufacturing processes.
- Discusses sustainability and industry 4.0 based contents.
- Includes case studies and practical examples.
This book is aimed at researchers and graduate students in Mechanical, Manufacturing, Production, and Industrial Engineering.
Zielgruppe
Academic and Postgraduate
Autoren/Hrsg.
Weitere Infos & Material
Chapter 1. Introduction to Process Modeling and Optimization in Modern Manufacturing: An Overview
Chapter 2. Recent Advances in the Applications of Machine Learning Optimization Techniques in Modern and Hybrid Manufacturing for Quality, Sustainability, and Productivity: Some Case Studies.
Chapter 3. Modelling and Optimization of Abrasive Water Jet Machining Process on Surface Quality of green composite using Nature-Inspired Techniques methods: Comparative Study of TLBO, ABC and PSO Chapter 4. Machine Learning-Enabled Gesture Recognition in 3D Printed Robotic Prostheses: Advances in Electromyography Control
Chapter 5. Investigation of the AISI 1040 Steel Machining Characteristics with the Application of Cutting Fluid (Corn oil+ Al2O3) using the Taguchi-TOPSIS (T-T) Approach
Chapter 6. Optimization of Electro Discharge Machining Parameters for Additively Manufactured Composite (AlSi10Mg + Niobium Carbide (NbC)) Using Random Forest Algorithm
Chapter 7. Investigation, Modeling and Advanced Optimization of Additive Manufacturing Characteristics: A Study on Evolutionary Methods
Chapter 8. Analysis for development of High-performance polymer nanocomposites for FDM based Additive Manufacturing
Chapter 9. Machine Learning based Optimization for FDM Printed Poly Lactic Acid parts
Chapter 10. Experimental Investigation on Cutting Rate in µECDM of Si-based Pyrax Glass: Evolutionary Parametric Optimization and Surface Morphology
Chapter 11. Micro Drilling in Cu-based Shape Memory Alloy via µ-ECM: Influence of Input Variables and GWO, PSO based Advanced Optimization