Smart And Sustainable Manufacturing Systems For Industry 4 0

The current perspectives of smart and sustainable manufacturing systems hold important implications for current practices and understanding these concepts for further implications. This comprehensive reference text discusses both centralized and decentralized production systems, using variety of new cutting-edge approaches to solve the problem. The text covers simulation-based approaches including social network-based approaches, discrete event-based approaches, and knowledge based for smart and sustainable systems. It further covers mathematical models such as single-objective, multi-objective, and many-objective. The text discusses important topics including energy efficiency, transportation constrains for efficient and effective production, meta-heuristic and hybrid algorithms, and real-time monitoring and analysis for smart and sustainable production. This book- • Presents approaches to improve the objectives of sustain-ability and smart production systems. • Discusses Internet of Things (IoT) and Industrial Internet of Things (IIoT) concepts and its implementation for production systems. • Covers social network analysis method in distributed manufacturing systems. • Examines reckoning prognostics and diagnostics to monitor the health of the systems in perspective of distributed manufacturing. • Discusses aspects of Industry 4.0 in specific production systems. The text will be useful for graduate students and professional in the fields of mechanical engineering, production engineering, industrial engineering, and manufacturing.

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. Features Assists in the understanding of the shifting paradigm in manufacturing sector towards smart and sustainable practices Showcases contemporary technologies and their insurgence in existing industries Focuses on need, applications, and implementation framework for Industry 4.0 Encapsulates all that one has to learn about sustainability and its transformation in Industry 4.0 Real time case studies are presented

This book provides a comprehensive exchange of information on current developments in the field of sustainable management of manufacturing systems and Industry 4.0. The authors’ ambition is to establish channels of communication and disseminate knowledge among professionals working in smart manufacturing and related institutions. The book brings together world-leading academics and practitioners from the fields of engineering, infrastructure planning, manufacturing management, and economics. The unique combination of fields and disciplines focused on Industry 4.0 provides presents opportunities to create a bridge between science and practice.

This book gives an overview of the latest technologies in the Industry 4.0, using smart and autonomous systems driven by data and machine learning, to develop a sustainable approach to manufacturing. It includes the implementation of smart technological approaches in different manufacturing processes such as laser welding, additive manufacturing, equipment maintenance and inspection, automotive manufacturing, poultry processing, supply chain management, value stream mapping and development. This book caters to research experts and practitioners who are keen to realize the benefits of industry 4.0 to transform the manufacturing sector into a more sustainable-based state.

Design of Smart Manufacturing Systems covers the fundamentals and applications of smart manufacturing or Industry 4.0 system design, along with interesting case studies. Digitization and Cyber-Physical Systems (CPS) have vastly increased the amount of data available to manufacturing production systems. This book addresses the planning, modeling and experimentation of different decision-making problems as well as the conditions that affect manufacturing. In addition, recent developments in the design of smart manufacturing and its applications are explained, covering the needs of both researchers and practitioners. To fully navigate the challenges and opportunities of smart manufacturing systems, contributions are drawn from operations research, information systems, computer science and industrial engineering as well as manufacturing engineering. Addresses hot topics like cybersecurity and artificial intelligence in smart manufacturing systems Provides case studies that show how solutions have been applied in practice Explores how smart manufacturing systems may impact on operators

This book introduces the concept of sensing, smart and sustainable systems (S3 systems) to support the design and redesign of products, services, business and manufacturing processes, manufacturing systems, and enterprises. The concept of S3 systems theory is introduced and explained in detail to support designers and engineers in their development task. This approach is embraced in the implementation of emergent Information and communication technologies and artificial intelligence techniques. The text helps the reader to understand the relationship between intelligent manufacturing, S3 systems and Industry 4.0. It presents a review of current approaches to design and development of technology-based products. Finally, it enlarges on the sensing, smart and sustainable systems theory to give examples of S3 systems as case studies.

Business innovation and industrial intelligence are paving the way for a future in which smart factories, intelligent machines, networked processes and Big Data are combined to foster industrial growth. The maturity and growth of instrumentation, monitoring and automation as key technology drivers support Industry 4.0 as a viable, competent and actionable business model. This book offers a primer, helping readers understand this paradigm shift from industry 1.0 to industry 4.0. The focus is on grasping the necessary pre-conditions, development & technological aspects that conceptually describe this transformation, along with the practices, models and real-time experience needed to achieve sustainable smart manufacturing technologies. The primary goal is to address significant questions of what, how and why in this context, such as:What is Industry 4.0?What is the current status of its implementation?What are the pillars of Industry 4.0?How can Industry 4.0 be effectively implemented?How are firms exploiting the Internet of Things (IoT), Big Data and other emerging technologies to improve their production and services?How can the implementation of Industry 4.0 be accelerated?How is Industry 4.0 changing the workplace landscape?Why is this melding of the virtual and physical world needed for smart production engineering environments?Why is smart production a game-changing new form of product design and manufacturing?

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. Focusses on machine learning applications in Industry 4.0 ecosystem, such as resource optimization, data analysis, and predictions. Highlights the importance of the explainable machine learning model in the manufacturing processes. Presents the integration of machine learning and big data analytics from an industry 4.0 perspective. Discusses advanced computational techniques for sustainable manufacturing. Examines environmental impacts of operations and supply chain from an industry 4.0 perspective. 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.