Intelligent Manufacturing Management Systems: Oper ational Applications of Evolutionary Digital Techn ologies in Mechanical and Industrial Engineering
Description
The concepts that pertain to the application of digital evolutionary technologies in the sphere of industrial engineering and manufacturing are presented in this book. A few chapters demonstrate stepwise discussion, case studies, structured literature review, rigorous experimentation results, and applications. Further chapters address the challenges encountered by industries in integrating these digital technologies into their operational activities, as well as the opportunities for this integration.
In addition, the reader will find:
Systemic explanations of the unique characteristics of big data, cloud computing, and AI used for decision-making in intelligent production systems;
Highlights of the current and highly relevant topics in manufacturing management;
Structured presentations resolving the issues being faced by many real-world applications in a broad range of areas such as smart supply chains, knowledge management, intelligent inventory management, IoT adoption in manufacturing management, and more;
Intelligent techniques for sustainable practices in industrial waste management.
Audience
The book will be used by researchers, industry engineers, and data scientists/AI specialists working in industrial engineering, mechanical engineering, production engineering, manufacturing engineering, and operations and supply chain management. The book will also be valuable to the service sector industry, such as logistics and those implementing smart cities.
<b>INTRELLIGENT MANUFACTURING MANAGEMENT SYSTEMS</b>
<b>The book explores the latest manufacturing techniques in relation to AI and evolutionary algorithms that can monitor and control the manufacturing environment.</b>
The concepts that pertain to the application of digital evolutionary technologies in the sphere of industrial engineering and manufacturing are presented in this book. A few chapters demonstrate stepwise discussion, case studies, structured literature review, rigorous experimentation results, and applications. Further chapters address the challenges encountered by industries in integrating these digital technologies into their operational activities, as well as the opportunities for this integration.
In addition, the reader will find:
<ul><li>Systemic explanations of the unique characteristics of big data, cloud computing, and AI used for decision-making in intelligent production systems;</li><li>Highlights of the current and highly relevant topics in manufacturing management;</li><li>Structured presentations resolving the issues being faced by many real-world applications in a broad range of areas such as smart supply chains, knowledge management, intelligent inventory management, IoT adoption in manufacturing management, and more;</li><li>Intelligent techniques for sustainable practices in industrial waste management.</li></ul><b>Audience</b>
The book will be used by researchers, industry engineers, and data scientists/AI specialists working in industrial engineering, mechanical engineering, production engineering, manufacturing engineering, and operations and supply chain management. The book will also be valuable to the service sector industry, such as logistics and those implementing smart cities.
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V. P. Kommula, PhD, is an associate professor in the Department of Mechanical Engineering, University of Botswana. He has over 21 years of teaching experience and served in various positions with different universities in many countries. Kommula's research is in the area of lean manufacturing and productivity improvement by adopting digital technologies. He has published 42 research articles in peer-reviewed international journals.
Devendra K. Yadav, PhD, is an assistant professor in the Department of Mechanical Engineering, National Institute of Technology Calicut, Kerala, India. His current research interests include supply chain management, logistics performance measurement, and Industry 4.0 applications in supply chain domains.
Chithirai Pon Selvan, PhD, is an associate professor at Curtin University, Dubai. He has over 21 years of experience in teaching and has published more than 100 research articles in journals. His research interests are in the areas of machine design, optimization techniques, and manufacturing practices.
Jayakrishna Kandasamy, PhD, is an associate professor in the School of Mechanical Engineering, Vellore Institute of Technology University, India. He has published 47 journal articles in leading SCI journals, 22 book chapters, 85 contributions to refereed conference proceedings, and one edited book. Dr. Jayakrishna's research is focused on the design and management of manufacturing systems and supply chains to enhance efficiency, productivity, and sustainability performance.
<b>Kamalakanta Muduli</b>, <b>PhD</b>, is an associate professor in the Department of Mechanical Engineering, Papua New Guinea University of Technology, Papua New Guinea. He has over 15 years of academic and research experience and has published 40 papers in peer-reviewed international journals.
<b>V. P. Kommula, PhD,</b> is an associate professor in the Department of Mechanical Engineering, University of Botswana. He has over 21 years of teaching experience and served in various positions with different universities in many countries. Kommula's research is in the area of lean manufacturing and productivity improvement by adopting digital technologies. He has published 42 research articles in peer-reviewed international journals.
<b>Devendra K. Yadav, PhD, </b>is an assistant professor in the Department of Mechanical Engineering, National Institute of Technology Calicut, Kerala, India. His current research interests include supply chain management, logistics performance measurement, and Industry 4.0 applications in supply chain domains.
<b>Chithirai Pon Selvan, PhD, </b>is an associate professor at Curtin University, Dubai. He has over 21 years of experience in teaching and has published more than 100 research articles in journals. His research interests are in the areas of machine design, optimization techniques, and manufacturing practices.
<b>Jayakrishna Kandasamy, PhD, </b>is an associate professor in the School of Mechanical Engineering, Vellore Institute of Technology University, India. He has published 47 journal articles in leading SCI journals, 22 book chapters, 85 contributions to refereed conference proceedings, and one edited book. Dr. Jayakrishna's research is focused on the design and management of manufacturing systems and supply chains to enhance efficiency, productivity, and sustainability performance.