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This book reports on the latest research and applications in the fields of sustainable manufacturing and remanufacturing, as well as process planning and optimization technologies. It introduces innovative algorithms, methodologies, industrial case studies and applications. It focuses on two topics: sustainable manufacturing for machining technologies and remanufacturing of waste electronic equipment, and various methods are covered for each one, including macro process planning, dynamic scheduling, selective disassembly planning and cloud-based disassembly planning. The experimental analysis provided for every method explains the benefits, as well as how they are sustainable for various real-world applications. Further, a theoretical analysis and algorithm design is presented for each, accompanied by the contributors’ relevant research, including: •         step-by-step guides;  •         application scenarios;  •         relevant literature surveys;  •         implementation details and case studies; and  •         critical reviews on the relevant technologies. This book is a valuable resource for researchers in sustainable manufacturing, remanufacturing and product lifecycle management communities, as well as practicing engineers and decision-makers in industry and all those interested in sustainable product development. It is also useful reading material for postgraduates and academics wanting to conduct relevant research, and a reference resource for manufacturing engineers developing innovative tools and methodologies.

Production management --- Environmental aspects. --- Manufactures. --- Computer aided design. --- Industrial management-Environmen. --- Manufacturing, Machines, Tools, Processes. --- Computer-Aided Engineering (CAD, CAE) and Design. --- Sustainability Management. --- Energy Efficiency. --- CAD (Computer-aided design) --- Computer-assisted design --- Computer-aided engineering --- Design --- Manufactured goods --- Manufactured products --- Products --- Products, Manufactured --- Commercial products --- Manufacturing industries --- Computer-aided engineering. --- Industrial management—Environmental aspects. --- Energy efficiency. --- Consumption of energy --- Energy efficiency --- Fuel consumption --- Fuel efficiency --- Power resources --- Energy conservation --- CAE --- Engineering --- Data processing --- Energy consumption.

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Manufacturing processes --- Automation.

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This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.

Applied physical engineering --- Engineering sciences. Technology --- Artificial intelligence. Robotics. Simulation. Graphics --- fabrieken --- mineralen (chemie) --- mijnbouw --- ingenieurswetenschappen --- robots