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Wiley-VCH - Industrial Engineering
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Advanced Techniques in Porous Structure Design for Additive Manufacturing
Concise, practical guide presenting skills to integrate porous structure design with additive manufacturing requirements Part of Wiley's Additive Manufacturing Skills in Practice series and written with the industry practitioner in mind, Advanced Techniques in Porous Structure Design for Additive Manufacturing addresses the growing integration of porous structures and additive manufacturing, essential for applications in the biomedical, aerospace, and automotive fields in which porous structures are crucial due to their ability to deliver top-notch performance alongside lightweight characteristics. This book covers all areas of the subject and concludes with a series of specialized chapters devoted to simulation software, case studies, and future trends and emerging technologies. Each chapter features a design problem that presents an open-ended scenario to prompt readers to think through the real-world applications of the concepts and theories discussed and connect them to their own job roles. Sample topics discussed in Advanced Techniques in Porous Structure Design for Additive Manufacturing include: * Fundamentals of additive manufacturing, covering processes, materials, and design considerations * Mathematical modeling, covering optimization techniques and the finite element method * Multiscale topology optimization, shape optimization methods, and post-processing techniques * Software utilization in porous structure design, with information on how to program simulations * Porous structures in soft robotics, porous heat sinks, porous plates, and porous mechanical support structures With a blend of theoretical understanding and hands-on expertise in an emerging domain, Advanced Techniques in Porous Structure Design for Additive Manufacturing is an essential reference for industry professionals, researchers, and postgraduate students in universities, particularly those specializing in mechanical design and additive manufacturing. [224 Pages, Hardcover]
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Process Machinery Handbook
Process Machinery Handbook: For Field Personnel, Decision Makers, and Students equips newcomers and seasoned professionals with essential insights into the diverse world of process machinery, empowering them to understand unique performance characteristics, common failure modes, and effective strategies for enhancing reliability in their operations. Any professional working at a production site for any length of time knows that process machinery comes in a wide range of designs and sizes, but not all process machines are considered equal. Some machines are more critical to the process than others, some are small, some are very large, some spin fast, and some turn relatively slowly. The great diversity in their construction and application can be daunting to those new to the industry and sometimes even challenge machinery veterans. There are many common concepts that apply to all equipment types, but each equipment category has its own unique application and performance characteristics, including cavitation in liquid handling pumps, surging in centrifugal gas compressors, rotor instability in high-speed centrifugal compressors, and the effect of the compression ratio on a reciprocating compressor's the discharge temperature. It is also essential for users to understand how and why different types of machinery fail, keeping in mind that the common failure modes differ greatly between rotating machinery types. We know that by addressing the common types of failure modes associated with each machine type, we can achieve significant improvements in their reliability. The first step in organizing an effective machinery reliability program is committing to performing failure analyses and gathering failure statistics. These activities will help users learn how and why their machines are failing. The next step is to continuously modify machines, processes, and methods to avoid common failures. Process Machinery Handbook: For Field Personnel, Decision Makers, and Students gives students and professionals alike the tools they need to understand the fundamentals of working with rotating machinery. [752 Pages, Hardcover]
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Mathematics and Computer Science for Real-World Applications, Volume 4
Mathematics and Computer Science for Real-World Applications gives invaluable insights into how mathematical and computer sciences drive essential modern innovations that enhance everyday life, making it a must-read for anyone interested in the intersection of mathematics and technology and their real-world applications. Mathematical sciences are part of nearly all aspects of everyday life. The discipline has underpinned beneficial modern capabilities, including internet searches, medical imaging, computer animation, numerical weather predictions, and digital communication. Mathematics and computer science are constantly evolving and contributing to most areas of science and engineering, therefore, future generations of mathematical scientists should reassess the increasingly cross-disciplinary nature of the mathematical sciences. Mathematics and Computer Science for Real-World Applications presents current scientific and technological innovations from leading academics, researchers, and experts across the globe in mathematical sciences and computing. The volume will discuss new technical ideas and features that can be incorporated into day-to-day life for the benefit of society. A diversified spectrum of scientific advancements is discussed, including applications of differential and integral equations, computational fluid dynamics, nanofluids, network theory and optimization, control theory, machine learning, and artificial intelligence. Readers will explore diverse ideas and innovations in the field of computing and its growing connections to various fields of mathematics. [640 Pages, Hardcover]
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Integrating Neurocomputing with Artificial Intelligence
Integrating Neurocomputing with Artificial Intelligence provides unparalleled insights into the cutting-edge convergence of neuroscience and computing, enriched with real-world case studies and expert analyses that harness the transformative potential of neurocomputing in various disciplines. Integrating Neurocomputing with Artificial Intelligence is a comprehensive volume that delves into the forefront of the neurocomputing landscape, offering a rich tapestry of insights and cutting-edge innovations. This volume unfolds as a carefully curated collection of research, showcasing multidimensional perspectives on the intersection of neuroscience and computing. Readers can expect a deep exploration of fundamental theories, methodologies, and breakthrough applications that span the spectrum of neurocomputing. Throughout the book, readers will find a wealth of case studies and real-world examples that exemplify how neurocomputing is being harnessed to address complex challenges across different disciplines. Experts and researchers in the field contribute their expertise, presenting in-depth analyses, empirical findings, and forward-looking projections. Integrating Neurocomputing with Artificial Intelligence serves as a gateway to this fascinating domain, offering a comprehensive exploration of neurocomputing's foundations, contemporary developments, ethical considerations, and future trajectories. It embodies a collective endeavor to drive progress and unlock the potential of neurocomputing, setting the stage for a future where artificial intelligence is not merely artificial, but profoundly inspired by the elegance and efficiency of the human brain. [336 Pages, Hardcover]
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Artificial Intelligence and Machine Learning for Industry 4.0
This book is essential for any leader seeking to understand how to leverage intelligent automation and predictive maintenance to drive innovation, enhance productivity, and minimize downtime in their manufacturing processes. Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and artificial intelligence. Artificial intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. The significance of AI is not found in its computational models, but in how humans can use them. Consistently observing equipment to keep it from malfunctioning is the procedure of predictive maintenance. Predictive maintenance includes a periodic maintenance schedule and anticipates equipment failure rather than responding to equipment problems. Currently, the industry is struggling to adopt a viable and trustworthy predictive maintenance plan for machinery. The goal of predictive maintenance is to reduce the amount of unanticipated downtime that a machine experiences due to a failure in a highly automated manufacturing line. In recent years, manufacturing across the globe has increasingly embraced the Industry 4.0 concept. Greater solutions than those offered by conventional maintenance are promised by machine learning, revealing precisely how AI and machine learning-based models are growing more prevalent in numerous industries for intelligent performance and greater productivity. This book emphasizes technological developments that could have great influence on an industrial revolution and introduces the fundamental technologies responsible for directing the development of innovative firms. Decision-making requires a vast intake of data and customization in the manufacturing process, which managers and machines both deal with on a regular basis. One of the biggest issues in this field is the capacity to foresee when maintenance of assets is necessary. Leaders in the sector will have to make careful decisions about how, when, and where to employ these technologies. Artificial Intelligence and Machine Learning for Industry 4.0offers contemporary technological advancements in AI and machine learning from an Industry 4.0 perspective, looking at their prospects, obstacles, and potential applications. [336 Pages, Hardcover]
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