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Modeling and Simulation in Industrial Engineering
This book describes the latest research developments in modeling and simulation in industrial engineering. Topics such as decision and performance analysis and industrial control systems are described. Case studies in industry and services as well as engineering economy and cost estimation are also covered.
Numerical Methods for Reliability and Safety Assessment
This book offers unique insight on structural safety and reliability by combining computational methods that address multiphysics problems, involving multiple equations describing different physical phenomena and multiscale problems, involving discrete sub-problems that together describe important aspects of a system at multiple scales. The book examines a range of engineering domains and problems using dynamic analysis, nonlinear methods, error estimation, finite element analysis and other computational techniques. This book also: · Introduces novel numerical methods · Illustrates new practical applications · Examines recent engineering applications · Presents up-to-date theoretical results · Offers perspective relevant to a wide audience, including teaching faculty/graduate students, researchers and practicing engineers.
Operational Perspective of Modeling System Reliability
This book provides insights into contemporary issues and challenges concerning operational research and related mathematical modeling fundamentals, such as system reliability, scalability, and adaptability. This collaboration of academia and industry disseminates practical tools and analytics applications of mathematics in engineering and information sciences Optimization techniques have gained popularity among system managers for making crucial decisions while meeting multiple needs. The focus of this book is the evaluation and optimization of critical decisions related to the system betterment. Each chapter presents the recent advancements and research opportunities in system assurance. Operational Perspective of Modeling System Reliability (Research Tools for System Dynamics) is for academicians and those who need to understand the latest developments in the field of System Reliability. Along with these, anyone solving problems within the related application domains will benefit from this compilation.
Reliability Assessment and Optimization of Complex Systems
Reliability Assessment and Optimization of Complex Systems delves into a range of tools and techniques for designing optimized complex systems. Each chapter explores system modeling and the implementation of various metaheuristics for optimization purposes. This book provides readers in the domain of applied mathematics with a comprehensive understanding of system reliability analysis and improvement, thereby offering substantial value to their knowledge and expertise. System reliability has become the paramount attribute of any production unit. The process of maximizing system reliability while adhering to multiple constraints is referred to as reliability optimization.There are two primary approaches to enhancing a system's performance and reliability: developing a product with reduced failures (failure avoidance) or incorporating resilience to ensure the system continues functioning even in the event of a failure (fault tolerance). - Explains the process and application of reliability-based design optimization - Covers many metaheuristic approaches such as reliability, cost, and the MTTF of the system - Provides the workings and applications of multi-objective optimizations
Machine Learning for Cyber Security
This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.
Mathematical Modelling of System Resilience
Almost all the systems in our world, including technical, social, economic, and environmental systems, are becoming interconnected and increasingly complex, and as such they are vulnerable to various risks. Due to this trend, resilience creation is becoming more important to system managers and decision makers, this to ensure sustained performance. In order to be able to ensure an acceptable sustained performance under such interconnectedness and complexity, resilience creation with a system approach is a requirement. Mathematical modeling based approaches are the most common approach for system resilience creation.Mathematical Modelling of System Resilience covers resilience creation for va...
Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science. The book Discusses basic as well as advance research in the field of prognostics Explores integration of data collection, fault detection, degradation modeling and reliability prediction in one volume Covers prognostics and health management (PHM) of engineering systems Discusses latest approaches in the field of prognostics based on machine learning The text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science.
Advanced Manufacturing Processes
The field of manufacturing science has evolved over the years with the introduction of non-traditional machining processes. This reference book introduces the latest trends in modeling and optimization of manufacturing processes. It comprehensively covers important topics including additive manufacturing at multi-scales, sustainable manufacturing, rapid manufacturing of metallic components using 3D printing, ultrasonic-assisted bone drilling for biomedical applications, micromachining, and laser-assisted machining. This book is useful to senior undergraduate and graduate students in the fields of mechanical engineering, industrial and production engineering, and aerospace engineering.
Differential Equations in Engineering
Differential Equations in Engineering: Research and Applications describes advanced research in the field of the applications of differential equations in engineering and the sciences, and offers a sound theoretical background, along with case studies. It describes the advances in differential equations in real life for engineers. Along with covering many advanced differential equations and explaining the utility of these equations, the book provides a broad understanding of the use of differential equations to solve and analyze many real-world problems, such as calculating the movement or flow of electricity, the motion of an object to and from, like a pendulum, or explaining thermodynamics concepts by making use of various mathematical tools, techniques, strategies, and methods in applied engineering. This book is written for researchers and academicians, as well as for undergraduate and postgraduate students of engineering.
Advances in Sustainable Machining and Manufacturing Processes
This text provides an in-depth overview of sustainability in machining processes, challenges during machining of difficult-to-cut materials and different ways of green machining in achieving sustainability. It discusses important topics including green and sustainable machining, dry machining, textured cutting coated tools for machining, solid lubricants-based machining, gas-cooled machining, cryogenic cooling for intelligent machining, artificial neural network for machining, big data based machining, and hybrid intelligent machining. This book- Covers advances in sustainable machining such as gas-cooled machining, near dry machining, and minimum quantity lubrication. Explores use of big da...
