The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.

This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.

This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

This book comprises the proceedings of International Conference on Research and Innovations in Mechanical Engineering (ICRIME 2013) organized by Guru Nanak Dev Engineering College, Ludhiana with support from AICTE, TEQIP, DST and PTU, Jalandhar. This international conference served as a premier forum for communication of new advances and research results in the fields of mechanical engineering. The proceedings reflect the conference’s emphasis on strong methodological approaches and focus on applications within the domain of mechanical engineering. The contents of this volume aim to highlight new theoretical and experimental findings in the fields of mechanical engineering and closely related fields, including interdisciplinary fields such as robotics and mechatronics.

The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.

This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.

This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

This book comprises the proceedings of International Conference on Research and Innovations in Mechanical Engineering (ICRIME 2013) organized by Guru Nanak Dev Engineering College, Ludhiana with support from AICTE, TEQIP, DST and PTU, Jalandhar. This international conference served as a premier forum for communication of new advances and research results in the fields of mechanical engineering. The proceedings reflect the conference’s emphasis on strong methodological approaches and focus on applications within the domain of mechanical engineering. The contents of this volume aim to highlight new theoretical and experimental findings in the fields of mechanical engineering and closely related fields, including interdisciplinary fields such as robotics and mechatronics.