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Gesamtkatalog

Catalogue complet

Reliability Engineering

Digital twins represent an emerging technology of immense potential across various industries. Their significance is particularly pronounced within Industry 4.0 and smart manufacturing paradigms, which strive to elevate efficiency and quality through seamless digital integration. By amassing and scrutinizing extensive data streams, digital twins empower data-centric decision-making-a pivotal asset in contemporary industry. Digital Twins of Advanced Materials Processing bridges the gap in comprehensive resources concerning advanced materials processing, a domain characterized by rapid evolution. It provides pragmatic remedies and real-world case studies, catering to tangible implementation needs. Moreover, digital twins hold the capacity to amplify efficiency and innovation within materials processing-a perspective deeply explored within this book, rendering it invaluable for professionals, researchers, and students alike. The prospects of employing digital twins in materials processing span diverse horizons: refining materials innovation, streamlining processes, enabling data-driven maintenance, enhancing product quality, and unearthing insights rooted in data. The book also undertakes the challenge of addressing key issues encompassing data amalgamation and integrity, model validation and calibration, software and data safeguarding, scalability, and cost considerations.

Digital Twins of Advanced Materials Processing

Systems Innovation Book Series

We cannot manage and control what we cannot measure and assess. Lack of approppriate assessmen tools and measures have been cited as a major reason for project failures, in terms of cost, schedule, and quality. This book launches the methodology for assessing innovation using relevant and sustainable metrics, rubrics, and standards.

We cannot manage and control what we cannot measure and assess. Lack of approppriate assessmen tools and measures have been cited as a major reason for project failures, in terms of cost, schedule, and quality. This book launches the methodology for assessing innovation using relevant and sustainable metrics, rubrics, and standards.

Metrics, Rubrics, and Standards

Assessing Innovation

Smart Systems for a Sustainable Future

Environmental Monitoring with AI and IoT

Strategies for improving resilience, incorporating complexity theory, risk analysis, and systems thinking with a rigorous mathematical treatment The Science of Resilience delves into the fascinating field of resilience science, exploring how various systems, ranging from physical infrastructure to social networks, can withstand and recover from disruptions. This interdisciplinary subject combines principles from complexity theory, risk analysis, and systems thinking to understand and mitigate the impacts of events like natural disasters, cyber-attacks, and economic crises. By using mathematical models and real-world examples, the book provides practical tools and strategies for designing resilient systems that can adapt and thrive in the face of uncertainty. Written by a highly qualified author with significant experience in the field, this book: <ul> <li>Covers synchronization, bottleneck analysis, epidemic modeling, social network disinformation and how to counter it, and restructuring a system to increase resilience</li> <li>Explains phase change and shows how to apply it to general complex systems</li> <li>Integrates rigorous mathematical models with real-world applications through mini case studies and hypothetical examples covering physical, economic, and social systems</li> <li>Provides tools and strategies to design resilient systems, analyze potential risks, and plain for resilience</li> </ul> Addressing an important gap in risk and resilience literature, this book offers valuable insights for engineering and systems design professionals, complexity science and risk analysis researchers, and graduate students in related fields, as well as anyone interested in the science of resilience.

Complexity, Risk Modeling, and Systems

The Science of Resilience

Meeting the Global Challenges

Engineering Management

Process Plant Design for Chemical Engineers: Guide to Practical Aspects of Engineering Decision Making serves as a practical guide for making appropriate, evidence-based decisions in all elements of process design. Process design engineers need to make a very large number of choices during the design of a process plant. These decisions are crucial, yet there are many examples of very poor choices in real-world applications that have resulted in large financial losses, serious injury or even death. The objective of the book is to assist effective evidence-based decision making and minimize risk. This book provides descriptions and analysis of many examples of real applications from different industries as examples of good and bad decisions, particularly how the available information was used. The lessons learned from each example are considered and described to help engineers understand the risks associated with process design decisions and how to manage them effectively. The book serves as a valuable resource for both chemical engineering students and engineers in industry as it provides guidance on making evidence-based decisions to ensure successful outcomes. It will also be incredibly helpful to engineers faced with the task of scaling up a new process based on lab-scale research, especially those tasked with plant design and designing commercial scale processes. This book can also be a useful guide for students and engineers in a range of process industries such as chemical processing, minerals processing, food and wine, , energy engineering, and similar related engineering fields.

Guide to Practical Aspects of Engineering Decision Making

Process Plant Design for Chemical Engineers

As data is the most important asset for any organization, it is essential to apply analytics to fulfill the sustainability needs of any organization. This book aims to provide a context for data analytics for the sustainability of organizations demonstrating innovation across a few specific subject areas with detailed coverage. It highlights how data analytics enables organizations to create intelligence by exploring opportunities and overcoming challenges, both present and future.Data Science: Semantic Technology, Intelligent Data Analytics, and Sustainability Practice is packed with up-to-date examples and data, ensuring it's both meaningful and practical for a diverse audience. It begins with an introduction to data analytics in the context of sustainable development. Each chapter explores the different aspects of data analytics for sustainability, utilizing a state-of-the-art context that is easy to grasp. Key concepts are presented through clear explanations, making them accessible to all readers. At the end of each chapter, is a summary of the main points, allowing for quick reviews of the essential ideas. It provides practical insights into applying data analytics concepts towards sustainable development, empowering readers to enhance their decision-making abilities, and discusses a strategic approach aligned with the vision for 2030 and beyond while addressing the anticipated challenges.This resource provides support to researchers, scholars, technology practitioners, business analysts, data scientists, and industry professionals worldwide, promoting globalization and enabling real-life application of findings in their organizations.

Semantic Technology, Intelligent Data Analytics, and Sustainability Practices

Data Science

Sustainable Industrial Engineering and Management Systems

Navigating the Future

Security Paradigms in 6G Smart Cities and IoT Ecosystems

The fourth industrial revolution places a number of additional demands on the design and automation of processing machines. Digitalization and automation are making products and their manufacturing processes not only more sophisticated, but also more individual. Growing demands on availability, logistics, quality and extreme price sensitivity are not leaving the production environment unscathed. This book analyses the challenges and provides meaningful examples of solution scenarios for effective production in the age of Industry 4.0.

Automation 4.0 shows readers how the requirements of Industry 4.0 may be projected onto known design principles. The resulting functions are illustrated using real-life examples from industry to create a roadmap for drawing up a specification sheet for the design of a versatile processing machine. Numerous practical examples illustrate the modular, function- and object-oriented design of individual machines and systems as a solution for increasing efficiency throughout their entire life cycle. To this end, a procedure for the design of versatile machines based on object- and function-oriented modularization is presented and illustrated and elaborated step by step on the basis of the requirements.

This book presents solution strategies that address the additional demands of modularization on the structure and component selection of automation systems flexibly, sustainably and with minimal engineering effort. These include aspects of real-time capability as well as machine safety and the selection of a suitable fieldbus, human-machine communication and the ability to interact in digital production. Finally, the topics of AI-supported quality assurance, simulation and digital twins are also addressed and the current state of research on the interaction of Industry 4.0 components is conveyed.

The book offers a comprehensive overview of the development of sustainable machines, particularly in terms of cost-effectiveness for very small batch sizes. It is not only for students of automation technology and mechatronics, but also for industrial, development and design engineers.

Automation 4.0: Object-oriented Development Of Modular Machines For Digital Production

Multifidelity Modeling in Vibration Analysis teaches users how to make predictions about physical systems in a computationally inexpensive manner.

Multifidelity Modeling in Vibration Analysis teaches users how to make predictions about physical systems in a computationally inexpensive manner.

Multifidelity Modeling in Vibration Analysis

Based on practical field experience and several case studies, this book presents state-of-the-art artificial intelligence techniques, validating their efficiency and accuracy in real-world industrial applications. The authors show how a meta-heuristic approach can enhance automatic fault monitoring in man-made systems. For each phase of fault monitoring, they propose a meta-heuristic approach that is tested experimentally in an actual industrial environment. While the proposed methods are validated on specific industrial problems, their applicability is wide and general.

Based on practical field experience and several case studies, this book presents state-of-the-art artificial intelligence techniques, validating their efficiency and accuracy in real-world industrial applications. The authors show how a meta-heuristic approach can enhance automatic fault monitoring in man-made systems. For each phase of fault monitoring, they propose a meta-heuristic approach that is tested experimentally in an actual industrial environment. While the proposed methods are validated on specific industrial problems, their applicability is wide and general.

Using Meta-Heuristic Optimization

Automatic Monitoring, Fault Diagnostics, and Maintenance

Industrial explosions can occur anywhere where combustible powders and/or flammable vapours are handled, such as facilities dealing with wood, flour, starch, sugar, rubber, plastics, pharmaceuticals, oil, gas, and other industries. Explosions can lead to loss of lives and colossal costs to companies found culpable for failing to follow safety protocols.Explosion Safety for Industries presents a set of preventative measures, rules, and standards to mitigate the risk of explosions by preventing potential explosive atmosphere formation. Coverage includes risks and hazards, equipment selection, earthing systems, static electricity, and lightning protection, among others. This book aims to help those responsible for the design, installation, operation and maintenance of process plants comply with the provisions of international safety legislation. Readers will develop a thorough understanding of the science behind explosions and the methods and measures needed to prevent accidents irrespective of their workplace or industry.This book is a comprehensive guide for industrial explosion prevention and protection for safety engineers, specialists, and managers as well as for physicists, chemists, mechanical engineers, and electrical engineers.

Prevention and Protection

Explosion Safety for Industries

Reliability Engineering

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