Machine Learning for Advanced Manufacturing

1. Auflage 2025
ISBN: 978-1-032-79689-5
Verlag: Taylor & Francis Ltd

Buch, Englisch, 216 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Advanced Materials Processing and Manufacturing

This book presents the use of Machine Learning and Artificial Intelligence in advanced and new manufacturing processes including core concepts and techniques of machine learning. It covers recent developments and research breakthroughs of tribological properties of polymer, metals, and ceramic based additive manufactured components. It details the various technologies available to fortify the machine learning aspects in the advanced manufacturing processes, focusing on multidisciplinary domains of science and technology.

Features:

- Establishes relationship between machine learning (ML) and advanced manufacturing (AM) technology.

- Helps understand the challenges and opportunities of using ML in materials processing, selection, and manufacturing for different areas.

- Reviews hybridization of techniques under ML for prediction and optimization for quality, productivity, and sustainability in manufacturing.

- Provides a comprehensive overview of the state-of-the-art, future directions, latest developments, and recent developments in ML for AM.

- Covers the basics of machine learning with implementation procedure and effectiveness details to provide a roadmap.

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

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Verma, Amit

Ranjan, Nishant

Tripathi, Ashutosh

Tyagi, Rashi

Kumar, Ranvijay

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Preface

Editors' Biography

List of Contributors

Acknowledgement

- Introduction to Machine Learning in Advanced Manufacturing

- Overview of different Machine Learning Techniques and algorithms for Data Acquisition and Pre-processing in advanced Manufacturing

- Recent advancement of Machine learning in Machining/Joining/Forming processes

-  Machine Learning for Product Design and Customization in Advance Manufacturing Practices

- Machine Learning in Additive Manufacturing

- Application of Machine Learning Beyond Manufacturing

-  Real-time Monitoring and Control Using Machine Learning in Industry

- Emerging Applications of Machine Learning in the Manufacturing Sector

- Prediction of Drilling Process Parameters While Machining Arhar Composite Using Random Forest Machine Learning Algorithm

- Beyond Manufacturing: The Expansion of Machine Learning Applications

Index

Über Autor(innen)

Nishant Ranjan is working as Assistant Professor at University Centre for Research and Development of Chandigarh University. He has won CII MILCA AWARD in the field of Additive Manufacturing in 2022. He has completed his PhD in Mechanical engineering from Punjabi University, Patiala, India. Fused deposition-modelling, extrusion, thermoplastic polymers, composition of thermoplastic polymers, natural and synthetic biopolymers, scaffolds printing, 3D printing technology, thermal, mechanical, morphological, and chemical properties of thermoplastic polymers, biocompatible and biodegradable fillers, reinforcement of materials are the main focus area of Nishant Ranjan.

Rashi Tyagi is currently working as an Assistant Professor in University centre for Research and Development at Chandigarh University. Dr. Tyagi has won CII MILCA AWARD in the field of electrical discharge coating in 2022. Dr. Tyagi has completed his PhD in Mechanical engineering from Indian Institute of Technology (Indian school of mines), Dhanbad, India. Her PhD work was focused on the surface modification by electrical discharge process for solid lubrication and enhanced tribological performance.

Ranvijay Kumar is an assistant professor in University Centre for Research and Development, Chandigarh University. He has received PhD in Mechanical Engineering from Punjabi University, Patiala. Additive manufacturing, shape memory polymers, smart materials, friction-based welding techniques, advance materials processing, polymer matrix composite preparations, reinforced polymer composites for 3D printing, plastic solid waste management, thermosetting recycling and destructive testing of materials are the skills of Kumar.

Ashutosh Tripathi is currently working as an Assistant Professor in University centre for Research and Development at Chandigarh University. He has worked in the field of composite preparation and simulation in 2022. He has completed his PhD in Mechanical engineering from Indian Institute of Technology (Indian school of mines), Dhanbad, India. His research work was focused on the acoustics properties of composite and its analytical prediction. He has completed his M.tech from IIT(ISM), Dhanbad, India.

Amit Verma is an accomplished Associate Professor at the School of Computer Science & Engineering (CSE) and the University Research Department at Bahra University. With over 12 years of academic experience, He has made significant contributions to the field of Artificial Intelligence (AI), particularly focusing on its applications in agriculture. His current research revolves around the detection of plant leaf diseases using advanced image processing and deep learning techniques.