Intelligent and sustainable manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. Other goals sometimes include fast changes in production levels based on demand, optimization of the production system, efficient production, and recyclability. This handbook provides compiled knowledge of intelligent and sustainable manufacturing within the context of Industry 4.0. along with tools, principles, and strategies.

Handbook of Intelligent and Sustainable Manufacturing: Tools, Principles, and Strategies offers recent developments, future outlooks, and advanced and analytical modeling techniques of intelligent and sustainable manufacturing with examples backed up by experimental and numerical data. It bridges the gap between R&D in intelligent and sustainable manufacturing–related fields and presents case studies and solutions alongside social and green environmental impact. The handbook includes a wide range of advanced tools and applications with modeling results and explains how different internet technologies integrate the manufacturing approach with people, products, and complex systems. By encompassing advanced technologies such as digital twins, big data informatics, artificial intelligence, nature-inspired algorithms, IoT, Industry 4.0, simulation approaches, analytical strategies, quality tools, roots and pillars, diagnostic tools, and methodical strategies, this handbook provides the most up-to-date and advanced information source available.

This handbook will help industries and organizations to implement intelligent manufacturing and move towards the sustainability of manufacturing practices. It will also serve as a reference for senior graduate-level courses in mechanical, production, industrial, and aerospace engineering and a value-added asset to libraries of all technical institutions.

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Yes, you can access Handbook of Intelligent and Sustainable Manufacturing by Ajay Kumar,Parveen,Yang Liu,Rakesh Kumar in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Industrial Engineering. We have over one million books available in our catalogue for you to explore.

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Publisher

Year

Print ISBN

eBook ISBN

Edition

Topic

Technology & Engineering

Subtopic

Industrial Engineering

Index

Technology & Engineering

Cover
Half Title
Series
Title
Copyright
Contents
Preface
Acknowledgments
Editors
Contributors
Chapter 1 Sustainable Manufacturing Practices in the Intelligent Manufacturing Era: A MICMAC Analysis of Roadblocks in Indian SMEs
Chapter 2 Human–Robot/Machine Interaction for Sustainable Manufacturing: Industry 5.0 Perspectives
Chapter 3 Nature-Inspired Optimization Techniques of Industry 4.0 for Sustainable Manufacturing
Chapter 4 Framework for Implementation of Disruptive Emerging ICTs in Intelligent and Sustainable Manufacturing in a Developing Context
Chapter 5 Digital Twins and IoT for Sustainable Manufacturing: A Survey of Current Practices and Future Directions
Chapter 6 Overview of Cyber Security in Intelligent and Sustainable Manufacturing
Chapter 7 Service Quality Improvement Using Fuzzy Inference Systems and Genetic Algorithm
Chapter 8 Identifying and Prioritizing Quality 4.0 Practices in Sustainable Manufacturing Using Rough Number-Based AHP-MABAC
Chapter 9 Intelligent Manufacturing in the Context of Industry 4.0 in Belarus: Overview and Perspectives
Chapter 10 Investigation of the Chip Reduction Coefficient of X-625 Using Coated Tools
Chapter 11 Effect of ECM, Hard Turning, and Deep Cryogenic on Properties of AISI S-1 Tool Steel
Chapter 12 A Study on Adoption of Information and Communication Tools in Emergency Disaster Management
Chapter 13 Optimization of Process Parameters of Counterbore Hole Made on Workpiece of Al-6061 Using DOE and MCDM Techniques
Chapter 14 Application of IoT and Artificial Intelligence in Smart Manufacturing: Towards Industry 4.0
Chapter 15 Intelligent Manufacturing in the Financial Sector: Applications in Asset Management and Trading
Chapter 16 Machine Learning Applications in Industry 4.0: Opportunities and Challenges
Chapter 17 Intelligent and Sustainable Manufacturing Applications in the Automotive Industry
Index

About this book

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Table of contents