Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Production engineering --- Mechanical engineering

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Manufacturing accounts for a significant portion of energy expenditure. Thus, energy efficient and environmentally friendly (EEEF) manufacturing practices are of significant importance. Sustainability plays a key role to manufacturing, becoming a major factor for manufacturers to be competitive in the global market. It would not only be important to the energy and environmental sectors, but also be substantially beneficial to society and economy. Sustainable manufacturing covers a broad spectrum of manufacturing, including both implementation of advanced manufacturing technology and developing energy-efficient manufacturing systems, as well as extension of product life cycle. Automation, as a vital factor to the success of sustainable manufacturing, plays a critical role. In recent years, it has attracted substantial effort from researchers in both academia and industry to provide efficient scientific and engineering solutions for sustainable manufacturing. This edited book of Sustainable Production Automation presents the recent development of innovative algorithms, models, heuristics, and techniques for production control and operation management in the area of sustainable manufacturing systems. In addition to overviews of recent development in sustainable manufacturing technology and practices, optimization and control methodologies for energy efficient manufacturing are the focuses in this volume. Remanufacturing system modeling and analysis, which are key elements for product life cycle, are also studied. We expect this volume can stimulate more original, significant, visionary, and in-depth research in sustainable production automation, to improve process, efficiency, productivity, quality, and reliability in manufacturing.

Production engineering. --- Sustainable engineering.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques Presents case studies involving enterprise, business, and government service deployment of big data applications Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data

Software engineering. --- Computer software engineering --- Engineering

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Industrial engineering

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Requirements engineering.