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Books in General engineering

Our General Engineering collection provides a broad foundation across multiple engineering disciplines, including fundamentals, design principles, and interdisciplinary innovations. It supports researchers, students, and professionals with essential tools and insights to tackle complex engineering challenges, foster innovation, and integrate emerging technologies such as AI, sustainability practices, and smart manufacturing.

BooksJournals

    • Biomechanics of Orofacial Organs and Structures

      • 1st Edition
      • May 1, 2026
      • Mohammad Ali Nazari + 2 more
      • English
      • Hardback
        9 7 8 0 4 4 3 2 1 6 0 9 1
      • eBook
        9 7 8 0 4 4 3 2 1 6 0 8 4
      Biomechanics of Orofacial Organs and Structures provides fundamental knowledge in functional anatomy and innervation of the orofacial region, in mechanical characteristics of orofacial soft tissues, in the biomechanical modeling of the orofacial organs, and in their use in the context of clinical applications. The book covers the design of biomechanical models that take into account the anatomy, muscle organization, innervation, and specific mechanical properties of muscles and soft tissue. It also discusses how these functions work under normal conditions, and how they degrade after surgery in the context of aging, or in the context of neuropathy altering the efferent or afferent nervous system in the orofacial region.The book is organized into three parts:General knowledge about orofacial organs and structuresBiomechani... modelsClinical applicationsA new volume in the Biomechanics of Living Organs series, this book features the latest research developments in the truly multidisciplinary scientific domain that tackles the understanding and modeling of basic orofacial functions, which are essential for the quality of life of humans.

    • Applied Artificial Intelligence for Engineering Applications

      • 1st Edition
      • May 1, 2026
      • Tarek Saadawi + 5 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 4 3 3 8 1
      • eBook
        9 7 8 0 4 4 3 4 4 3 3 9 8
      Applied Artificial Intelligence for Engineering Applications: Empowering Transformative Innovations in Multidisciplinary Engineering offers an integrated view of AI’s transformative potential in multidisciplinary engineering, bridging the gap between AI advances and their applications in various engineering disciplines, including civil, mechanical, electrical, chemical, and robotics. The book starts with an introduction to the field, providing an overview of AI technologies and their relevance to engineering, discussing different AI approaches such as machine learning, reinforcement learning, neural networks, and natural language processing. Computational tools and software used for each of these approaches are covered, as are AI-driven innovations in electronics design and manufacturing as well as the role of AI in the development of advanced sensors and IoT devices. Chapters then cover the deployment of AI in specific engineering disciplines, outlining its use in civil engineering, mechanical engineering, production engineering, and chemical engineering. The use of AI as a solution for energy efficiency and management and renewable energy integration is also discussed.

    • Manufacturing

      • 2nd Edition
      • April 28, 2026
      • Erik Tempelman + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 2 0 3 6
      • eBook
        9 7 8 0 4 4 3 3 3 2 0 2 9
      Manufacturing: Design, Science and Engineering of How Things are Made, Second Edition offers a comprehensive exploration of modern industrial production. Opening with a discussion on the importance of abstraction levels and the necessity of balancing trade-offs, the book challenges readers to analyze manufacturing processes from multiple perspectives. By examining what is theoretically possible under physical laws, what can be achieved with current industrial methods, and what is feasible for specific suppliers, the text equips engineers and designers with practical insights. This approach enables readers to optimize design choices and production strategies in real-world manufacturing settings.Beyond its foundational framework, the book covers a wide range of manufacturing processes, including metal forging, extrusion, casting, plastic injection molding, thermoforming, additive manufacturing, joining, and recycling. It emphasizes the critical role of understanding supplier capabilities when seeking optimal production solutions. The material encourages readers to develop not only producible designs but also deeper partnerships with suppliers.

    • Digital Twins of Advanced Materials Processing

      • 1st Edition
      • April 1, 2026
      • Tarasankar DebRoy + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 2 9 1 8 0
      • eBook
        9 7 8 0 4 4 3 3 2 9 1 9 7
      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.

    • Artificial Intelligence Methods in Railway Infrastructure Systems

      • 1st Edition
      • March 1, 2026
      • Diogo Ribeiro + 5 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 7 7 9 6
      • eBook
        9 7 8 0 4 4 3 3 3 7 8 0 2
      Artificial Intelligence Methods in Railway Infrastructure Systems: Application of Data Centric Engineering offers a thorough exploration of the latest advancements transforming railway management. With a strong focus on practical and theoretical approaches, this book introduces innovative AI techniques including machine learning, computer vision, and predictive analytics. These methodologies are presented in the context of railway infrastructure, empowering engineers and researchers to utilize cutting-edge technology for enhanced system reliability. By bridging the gap between theory and real-world applications, the book enables early detection of anomalies, supporting proactive maintenance strategies and improved operational efficiency in railway networks.This book acts as a vital reference for those seeking to understand and implement AI-driven solutions in railway systems, encouraging the adoption of anticipatory strategies to shape future trends. Readers will discover how AI innovations can streamline operations, optimize resource allocation, and significantly improve network safety, making it an essential guide for professionals looking to stay ahead in the evolving field of railway infrastructure management.

    • BioMEMS Devices

      • 1st Edition
      • February 1, 2026
      • Azrul Azlan Hamzah + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 0 1 5 7
      • eBook
        9 7 8 0 4 4 3 2 4 0 1 4 0
      BioMEMS Devices covers the fundamentals of bioMEMS and discusses how MEMS are implemented into biomedical devices. The book discusses the most up-to-date technologies, including the various types of electrochemical, optical, and mechanical MEMS sensors. Other topics include bio cell and particle separation and filtration using microfluidic platform such as dielectrophoresis (DEP) and microfilters. MEMS devices for drug mixing, pumping and transdermal drug delivery using microneedles and micropumps are also discussed, along with recent advances in point-of-care diagnostics and MEMS in medical implantsThe book concludes with a discussion on integration of bioMEMS system with IoT, medical practitioners’ adaptation of the devices, market penetration, emerging technologies, and future outlooks.

    • Industrial Fault Diagnosis and Remaining Useful Life Prediction

      • 1st Edition
      • February 1, 2026
      • Hongpeng Yin + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 4 2 9 1 9
      • eBook
        9 7 8 0 4 4 3 4 4 2 9 2 6
      Industrial Fault Diagnosis and Remaining Useful Life Prediction: Cross-Domain, Zero-Sample, and Degradation Modeling Methods introduces zero-sample learning methods that enable fault diagnosis and Predict Remaining Useful Life (RUL) without the need for labelled fault data. This is particularly valuable in industrial settings where labelled data is scarce or unavailable. Offers step-by-step guidance on implementing zero-shot learning models using real industrial data, reducing the learning curve for practitioners; includes real-world industrial case studies to demonstrate the application of zero-sample learning techniques in various industries, such as manufacturing, energy, and transportation. Such case studies provide readers with actionable insights and practical solutions. The book covers advanced methodologies for predicting the remaining useful life of industrial equipment, supporting readers in optimizing maintenance schedules, reducing downtime and extending the lifespan of critical assets. Covers state-of-the-art algorithms, including deep learning, transfer learning and domain adaptation, tailored for zero-sample scenarios. These tools empower readers to develop robust fault diagnosis and RUL prediction systems, enhancing predictive maintenance capabilities and ensuring the reliability of industrial systems.

    • Engineering Materials for 3D Printing

      • 1st Edition
      • January 1, 2026
      • Rupinder Singh + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 6 2 5 6
      • eBook
        9 7 8 0 4 4 3 3 3 6 2 6 3
      3D printing processes have promising advantages over conventional manufacturing processes from a functional ability viewpoint. In the past 30 years, a variety of additive manufacturing-based 3D printing processes have been reported for the fabrication of functional prototypes, using materials such as thermoplastic, resins, metal and their alloys. While there is a significant amount of information on various 3D printing processes, and materials that may be used in 3D printing-based manufacturing practices for engineering applications, there is far less information on 3D printable materials for structural and non-structural engineering applications. Engineering Materials for 3D Printing fills this gap. The book includes three sections and provides an insight on the development and characterization of polymer-based 3D printed materials by different processes such as extrusion, sol-gel, and pulverization along with meta-structure properties for various structural applications

    • Network-Constrained Data-Driven Control of High-Speed Railway Systems

      • 1st Edition
      • January 1, 2026
      • Deqing Huang + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 8 9 9 4 5
      • eBook
        9 7 8 0 4 4 3 4 8 9 9 5 2
      Network-Constrained Data-Driven Control of High-Speed Rail Systems addresses the critical challenges in high-speed railway (HSR) operational control systems, focusing on enhancing safety, efficiency, and automation in an era of rapid network expansion. Railway systems face limitations in automatic driving capabilities and decentralized control, relying heavily on manual adjustments and outdated communication infrastructure like GSM-R (limited to 9.6 kbit/s speeds and 400 ms delays). Network-Constrained Data-Driven Control of High-Speed Rail Systems introduces a transformative framework for data-driven adaptive control and multi-train cooperative control under dynamic network constraints. It integrates next-generation 5G-R communication to enable real-time train-to-train (T2T) coordination, reducing dependency on fixed infrastructure and addressing vulnerabilities like faded channels and interference. By combining rigorous theoretical analysis with simulations, the book proposes solutions to improve operational precision, resilience against disruptions, and transportation capacity. This resource is helpful for researchers, engineers, and graduate students in high speed railway control systems, offering innovative strategies to advance autonomous operations and meet the demands of high-density, high-speed rail networks

    • The Control of Multiple Unmanned Aerial Vehicles

      • 1st Edition
      • January 1, 2026
      • Mingyang Xie + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 0 4 3 3 7
      • eBook
        9 7 8 0 4 4 3 4 0 4 3 4 4
      The Control of Multiple Unmanned Aerial Vehicles provides readers with a unified framework to address the challenges of multi-UAV target encirclement tracking control. This is achieved by comprehensively integrating the concepts of dynamic modelling, state and disturbance estimation, guidance law design, distributed control, obstacle avoidance and reinforcement learning-based formation tracking control with multi-UAV encirclement tracking systems. The book provides practical insight and solutions to the challenges of multi-UAV use, including limited sensing, communication constraint, wind disturbances and obstacle and collision avoidance, enabling readers to effectively apply the concepts to their work or research. Cutting-edge control techniques and advanced theories are explored, including robust distributed control, adaptive neural network approximation, reinforcement learning and multi-agent systems, presenting readers with state-of-the-art methodologies from which to develop practical applications of UAV formation. Each guidance and control method presented in the book is accompanied by a thorough comprehensive analysis to ensure that each is theoretically grounded. The book ensures transparency by providing open-access simulation codes, allowing readers to easily access and reproduce presented results.

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