Vimal K.E.K. – författare

Industry 4.0 promises tremendous opportunities for industries to go green by leveraging virtual physical systems and internet driven technologies for a competitive advantage and set the platform for the factory of the future and smart manufacturing. The book provides measures that can be adopted by practicing design engineers, to develop products that will be sustainable in all stages of its life cycle. It helps organizations in implementation of sustainable manufacturing practices and formulation of critical strategies in their transition towards Industry 4.0., and the book will provide insights on ways of deploying these practices in correlation with the environmental benefits mapped to support the practicing managers and stakeholders.FeaturesAssists in the understanding of the shifting paradigm in manufacturing sector towards smart and sustainable practicesShowcases contemporary technologies and their insurgence in existing industriesFocuses on need, applications, and implementation framework for Industry 4.0Encapsulates all that one has to learn about sustainability and its transformation in Industry 4.0Real time case studies are presented

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.