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Books in General engineering

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    • Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture

      • 1st Edition
      • January 1, 2026
      • Guozheng Kang + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 4 6 1 5 3
      • eBook
        9 7 8 0 4 4 3 4 4 6 1 6 0
      Machine Learning in the Analysis of Solid Deformation, Fatigue and Fracture fills a clear gap in literature by applying machine learning to deformation, fatigue, and fracture analysis in solid mechanics. The book’s focus on complex mechanisms and coupling phenomena, discussed with practical examples, makes it a valuable resource for advanced researchers. Practical examples and case studies enable readers to understand both the underlying engineering problems and the application of machine learning methods to enhance fatigue life prediction analysis for solid materials and structures.

    • 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

    • 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

    • 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.

    • Digital Twins of Advanced Materials Processing

      • 1st Edition
      • January 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.

    • Manufacturing

      • 2nd Edition
      • March 1, 2026
      • Erik Tempelman + 1 more
      • English
      Manufacturing: Design, Science and Engineering of How Things are Made, Second Edition, presents a fresh view on the world of industrial production: thinking in terms of both abstraction levels and trade-offs. The book invites its readers to distinguish between what is possible in principle for a certain process (as determined by physical law); what is possible in practice (the production method as determined by industrial state-of-the-art); and what is possible for a certain supplier (as determined by its production equipment). Specific processes considered here include metal forging, extrusion, and casting; plastic injection molding and thermoforming; additive manufacturing; joining; recycling; and more. By tackling the field of manufacturing processes from this new angle, this book makes the most out of a reader's limited time. It gives the knowledge needed to not only create well-producible designs, but also to understand supplier needs in order to find the optimal compromise. Apart from improving design for production, this publication raises the standards of thinking about producibility.

    • 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.

    • 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
      With the rapid recent advances in the field of railway systems and infrastructure construction, and the evolution of AI tools that have enormous potential for application to railway design, maintenance and operations, industry professionals and researchers need an up-to-date resource on these developments. Artificial Intelligence Methods in Railway Infrastructure Systems: Application of Data Centric Engineering addresses this need. The book encapsulates the latest breakthroughs and contributions in these pivotal areas, providing readers with comprehensive insights into the cutting-edge methodologies and approaches shaping the field of railway infrastructure management. For engineers and researchers, the book provides a focused explanation of AI methodologies such as machine learning, computer vision and predictive analytics and their implementation to railway infrastructure development, tools that are new to this field. It combines theory with practical examples of the application of data centric engineering in structural health monitoring of monitoring of railway systems, thus enabling early anomaly detection and empowering infrastructure managers to address potential issues before they escalate. Given the expansive scope of research driving technological advancements in railway infrastructure management, this book serves as a reference for readers seeking to explore novel AI-based methodologies and harness their potential in the field. Readers will benefit from insights into how AI innovations can streamline their operations and enhance network safety across multiple dimensions. By providing a comprehensive overview of the subject matter, this book guides anticipatory strategies and shape future trends in railway infrastructure management.

    • Network-Constrained Data-Driven Control of High-Speed Rail 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

    • Event-Driven State Estimation for Stochastic Networked Systems

      • 1st Edition
      • December 1, 2025
      • Cong Huang + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 5 0 1 4 3
      • eBook
        9 7 8 0 4 4 3 4 5 0 1 5 0
      Event-Driven State Estimation for Stochastic Networked Systems offers a comprehensive and clear explanation of recent developments in event-based state estimation for stochastic systems within limited communication networks, bringing together existing and emerging concepts. It provides a series of the latest results in, including but not limited to, recursive state estimation, fusion estimation, and state and fault estimation. The book provides practitioner readers with practical tools for the analysis and design of stochastic systems under limited communication networks, capturing recent advances in theory, technological aspects and real-world applications of advanced event-based state estimation methodologies. Realistic research problems are addressed in each chapter, with numerical and simulation results provided to reflect engineering practice, while demonstrating the main focus of the developed estimation approaches. The book is an advanced-level resource presented in an accessible manner, appealing to senior students as a core reference and to researchers and practitioners alike

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