Verkauf durch Sack Fachmedien

Pratap Singh / Kumar / Francis

Process Modeling and Optimization in Modern Manufacturing

Medium: Buch
ISBN: 978-1-032-58189-7
Verlag: CRC Press
Erscheinungstermin: 23.10.2025
Lieferfrist: bis zu 10 Tage

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. The focus of this book is on artificial neural network, finite element analysis, firefly/genetic algorithm, particle swarm, and fuzzy-based techniques, which are the main optimization and modeling techniques.

Features of the book:

- 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.

- Provides step-by-step guidance on how to use machine learning for the enhancement of productivity and quality in modern manufacturing processes.

- Discusses sustainability and Industry 4.0-based content.

- Includes case studies and practical examples.

This book is aimed at researchers and graduate students in mechanical, manufacturing, production, and industrial engineering.


Produkteigenschaften


  • Artikelnummer: 9781032581897
  • Medium: Buch
  • ISBN: 978-1-032-58189-7
  • Verlag: CRC Press
  • Erscheinungstermin: 23.10.2025
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2025
  • Serie: Advanced Materials Processing and Manufacturing
  • Produktform: Gebunden, HC gerader Rücken kaschiert
  • Gewicht: 487 g
  • Seiten: 210
  • Format (B x H x T): 161 x 240 x 16 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

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