Industrial Engineering, Systems, and Management – serie

The reference text discusses fundamental principles, planning, sourcing, demand forecasting, and supply forecasting in the field of supply chain management. It further highlights the important aspects of supply chain management such as resource planning, inventory management, quality tools, and documentation in logistics. It demonstrates the issues, barriers, emerging trends, and technological advances in supply chain management.This book:Discusses the principles of resource planning and inventory management in supply chain managementCovers aspects of competing strategies and networking managementPresents case studies highlighting ongoing practices and real-time issues in supply chain managementHighlights the importance of demand and supply forecasting in the field of supply chain managementExplains quality tools, emerging trends, challenges, and barriers in supply chain managementIt is written primarily for senior undergraduate and graduate students, and academic researchers in the fields of industrial engineering, production engineering, mechanical engineering, management, supply chain management, and manufacturing engineering.

The book highlights the importance of intelligent decision-making in advanced production systems, and optimization of process parameters using fuzzy-based multi-criteria decision-making tools. It discusses the decision-making aspects of Industry 4.0 using machine learning and optimization techniques and helps in moving toward the digitalization of manufacturing systems. It further covers several important topics including the role of digital twins in advanced manufacturing processes, machine learning-based prediction of overall equipment effectiveness, intelligent quality control tools, and life cycle assessment models in Industry 4.0.Key features:Presents a conceptual framework to measure the readiness of adopting Industry 4.0 in advanced manufacturing systems.Discusses the impact of smart manufacturing on sustainable development and integration of Industry 4.0 and additive manufacturing.Covers topics such as intelligent automation systems, machine learning-based preventive maintenance, and the Internet of Things-enabled additive manufacturing in Industry 4.0.Explains cyber-physical system integration with Industry 4.0 technologies, cyber-physical systems in industrial robotics, and green cyber-physical systems.Illustrates optimization of process parameters using fuzzy-based multi-criteria decision-making tools and life cycle assessment models in Industry 4.0.This book is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of industrial engineering, production engineering, mechanical engineering, supply chain management, and manufacturing engineering.

The book highlights the importance of intelligent decision-making in advanced production systems, and optimization of process parameters using fuzzy-based multi-criteria decision-making tools. It discusses the decision-making aspects of Industry 4.0 using machine learning and optimization techniques and helps in moving toward the digitalization of manufacturing systems. It further covers several important topics including the role of digital twins in advanced manufacturing processes, machine learning-based prediction of overall equipment effectiveness, intelligent quality control tools, and life cycle assessment models in Industry 4.0.Key features:Presents a conceptual framework to measure the readiness of adopting Industry 4.0 in advanced manufacturing systems.Discusses the impact of smart manufacturing on sustainable development and integration of Industry 4.0 and additive manufacturing.Covers topics such as intelligent automation systems, machine learning-based preventive maintenance, and the Internet of Things-enabled additive manufacturing in Industry 4.0.Explains cyber-physical system integration with Industry 4.0 technologies, cyber-physical systems in industrial robotics, and green cyber-physical systems.Illustrates optimization of process parameters using fuzzy-based multi-criteria decision-making tools and life cycle assessment models in Industry 4.0.This book is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of industrial engineering, production engineering, mechanical engineering, supply chain management, and manufacturing engineering.