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Inhaltsangabe
Transform your manufacturing operations for the Industry 4.0 era with this essential guide, which delivers the practical AI and soft computing strategies you need to master complexity, optimize efficiency, and build resilient, smart production systems.
The advancement of manufacturing technologies has consistently been linked to progress in modern computational methods. In recent years, the integration of soft computing techniques has emerged as an essential factor in improving the adaptability, intelligence, and efficiency of manufacturing processes. Unlike traditional deterministic approaches, soft computing methods are capable of managing complexity, uncertainty, and imprecision that are integral in current manufacturing systems, enabling more effective optimization, decision-making, and process control. This book provides an in-depth exploration of how soft computing techniques are transforming the landscape of modern manufacturing. Integrating intelligent computation with engineering principles, the book demonstrates how these methods enhance decision-making, optimize complex processes, and enable adaptive control across diverse manufacturing operations. Covering applications in machining, process planning, scheduling, quality assurance, and fault diagnosis, it bridges the gap between traditional manufacturing and the new era of Industry 4.0. It emphasizes the role of artificial intelligence, machine learning, and data-driven technologies in achieving precision, flexibility, and sustainability. Through detailed case studies, comparative analyses, and practical insights, the book provides readers with both theoretical foundations and implementation strategies. Ideal for engineers, researchers, and professionals in academia and industry, this book serves as a comprehensive guide to leveraging soft computing for smarter, more efficient, and resilient manufacturing systems, paving the way toward a future of intelligent and sustainable production.
Readers will find the volume:
- Integrates cutting-edge soft computing methods such as fuzzy logic, neural networks, and genetic algorithms for intelligent manufacturing solutions;
- Demonstrates real-world applications in process optimization, quality control, and predictive maintenance;
- Bridges the gap between traditional manufacturing and Industry 4.0 through adaptive and data-driven approaches.
Audience
Mechanical, industrial, and manufacturing engineers, materials scientists, and automation specialists across both academia and industry working in areas such as smart manufacturing, artificial intelligence in production, and Industry 4.0 technologies.
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Über die Autorin bzw. den Autor
Sandip Kunar, PhD is an Assistant Professor in the Department of Mechanical Engineering at the Aditya Engineering College, Andhra Pradesh, India. He has published more than 40 research papers in various reputed international journals, more than 25 research papers in national and international conference proceedings, 70 book chapters, 24 books, and two patents.
Elumalai P. V., PhD is a Professor in the Department of Mechanical Engineering at Aditya University, Andhra Pradesh, India with more than 12 years of experience. He has published more than 135 research papers in peer-reviewed journals and several book chapters.
Sridevi Gamini, PhD is an Associate Professor in the Department of Electronics and Communication Engineering at Aditya University, Andhra Pradesh, India. She has published 13 research papers in national and international journals and 10 research papers in reputed international conference proceedings.
S. Rama Sree, PhD is a Professor in the Computer Science and Engineering Department and Pro Vice-Chancellor of Academics at Aditya University, Andhra Pradesh, India. She has published 35 papers in international journals, 15 papers in national and international conferences, and four patents, and has co-authored one book.
M. Sreenivasa Reddy, PhD is the Director of the Aditya Group of Educational Institutions and the Deputy Pro Chancellor of Aditya University, Andhra Pradesh, India. He has published more than 50 research papers in various reputed international journals, national and international conference proceedings, 20 book chapters, three books, and eleven patents.
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Transform your manufacturing operations for the Industry 4.0 era with this essential guide, which delivers the practical AI and soft computing strategies you need to master complexity, optimize efficiency, and build resilient, smart production systems.
The advancement of manufacturing technologies has consistently been linked to progress in modern computational methods. In recent years, the integration of soft computing techniques has emerged as an essential factor in improving the adaptability, intelligence, and efficiency of manufacturing processes. Unlike traditional deterministic approaches, soft computing methods are capable of managing complexity, uncertainty, and imprecision that are integral in current manufacturing systems, enabling more effective optimization, decision-making, and process control. This book provides an in-depth exploration of how soft computing techniques are transforming the landscape of modern manufacturing. Integrating intelligent computation with engineering principles, the book demonstrates how these methods enhance decision-making, optimize complex processes, and enable adaptive control across diverse manufacturing operations. Covering applications in machining, process planning, scheduling, quality assurance, and fault diagnosis, it bridges the gap between traditional manufacturing and the new era of Industry 4.0. It emphasizes the role of artificial intelligence, machine learning, and data-driven technologies in achieving precision, flexibility, and sustainability. Through detailed case studies, comparative analyses, and practical insights, the book provides readers with both theoretical foundations and implementation strategies. Ideal for engineers, researchers, and professionals in academia and industry, this book serves as a comprehensive guide to leveraging soft computing for smarter, more efficient, and resilient manufacturing systems, paving the way toward a future of intelligent and sustainable production.
Readers will find the volume:
- Integrates cutting-edge soft computing methods such as fuzzy logic, neural networks, and genetic algorithms for intelligent manufacturing solutions;
- Demonstrates real-world applications in process optimization, quality control, and predictive maintenance;
- Bridges the gap between traditional manufacturing and Industry 4.0 through adaptive and data-driven approaches.
Audience
Mechanical, industrial, and manufacturing engineers, materials scientists, and automation specialists across both academia and industry working in areas such as smart manufacturing, artificial intelligence in production, and Industry 4.0 technologies.
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Soft Computing in Advanced Manufacturing Processes
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