Wiley-VCH - Industrial Engineering
A Passion for Publishing
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System Reliability Modeling
Technical, comprehensive resource on system reliability modeling System Reliability Modeling develops algorithms for generating a system reliability model using matrix algebra, with all algorithms presented in ready-to-use MATLAB functions ensuring system reliability modeling becomes as simple as writing a few lines of MATLAB code, no matter how complex the system structures are. All functions are managed in a user-friendly software package to simplify modeling and analyzing the reliability of a complex system. The package is also utilized to investigate the optimum maintenance and replacement programs, component orderings, and warmness levels in standby systems. The book includes examples and simple exercises for every topic, applications for real systems, problems at the end of each chapter, a chapter on discrete time systems, and a chapter on the use of AI in system reliability. This book discusses: * Matrix-based distributions, covering continuous-time Markov chains (CTMC), ways to model CTMC, phase-type (PH) and matrix-exponential (ME) distributions, similarity transformation, and approximating scalar distributions with PH distributions * One-component systems, covering reliability, hazard, and mean residual lifetime functions, perfect and imperfect maintenance, optimum replacement interval, and stock-out risk. * Basic structured systems, covering series, parallel, standby with perfect and imperfect switches structures, and any combination of these structures * General structure systems, covering a method to incorporate warmness levels into standby systems, so that one standby model applies to hot, warm, and cold standby in any combination thus applicable to all basic structured systems * Network reliability, covering methods for converting Boolean structure functions into arithmetic functions and calculating network's reliability measures and the maximum reliability function in capacitated networks System Reliability Modeling is an excellent resource for students, researchers, reliability engineers, maintenance engineers, and spare part logistics engineers seeking a rigorous analytical method in system design for reliability. [624 Pages, Hardcover]
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- Fault Diagnosis of Permanent Magnets Machines
- Analytics for Sustainable Refrigeration and Cold Supply Chains
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Computational Modelling of Additive Manufacturing
Enables readers to understand the additive manufacturing process-structure-property relationships and optimize the manufacturing parameters and machines via computational modeling techniques, including multi-physics modeling and data-driven analysis. Computational Modeling of Additive Manufacturing provides a step-by-step guide, covering topics from basic physics and governing equations to the implementation, experimental validation, model capability, and physical mechanisms obtained from simulation, as well as expert perspectives on future outlooks. With a well-rounded exploration of key areas, this book integrates various modeling techniques, including multi-physics modeling of powder, fluid and solid mechanics, heat transfer, microstructure evolutions, data-driven analysis including surrogate modeling, uncertainty quantification and multi-objective optimization, and a synergy of modeling with other techniques. Modeling of various additive manufacturing processes are included, such as laser/electron beam powder bed fusion, directed energy deposition, binder jetting, and material extrusion. The book presents comprehensive simulations covering a variety of issues for the process-structure-property relationships, including: * Multi-phase flow modeling of powder dynamics (e.g., spreading and spattering) in powder-bed-based additive manufacturing processes * Multi-physics modeling of molten pool dynamics in fusion-based additive manufacturing processes, with mechanistic heat source model, composition-dependent evaporation and chemical reaction models, and under external energy fields, as well as the thermal-fluid dynamics in other additive manufacturing processes. * Modeling of microstructure evolutions including grain and dendrite evolutions * Multi-scale modeling of thermal and residual stresses, and the room- and high-temperature mechanical properties of the additively manufactured parts * Data-driven surrogate modeling, uncertainty quantification and optimization, and the synergy with digital twins, smart diagnostics, and control This book is an essential first-of-its-kind reference for researchers in this specific area, and the larger area, of additive manufacturing who focus on experiments, materials design, mechanics, and other areas of interest. [496 Pages, Hardcover]
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- Smart and Sustainable Manufacturing
